Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-27T13:27:28.273Z Has data issue: false hasContentIssue false
  • English
  • Français

A Critical Review of Control Techniques for Flexible and Rigid Link Manipulators

Published online by Cambridge University Press:  05 May 2020

Esmail Ali Alandoli Open the ORCID record for Esmail Ali Alandoli [Opens in a new window]  and
T. S. Lee
Esmail Ali Alandoli*
Affiliation:
Faculty of Engineering and Technology, Multimedia University (MMU), 75450Melaka, Malaysia E-mail: tslee@mmu.edu.my
T. S. Lee
Affiliation:
Faculty of Engineering and Technology, Multimedia University (MMU), 75450Melaka, Malaysia E-mail: tslee@mmu.edu.my
*
*Corresponding author. E-mail: alandolie@yahoo.com
Rights & Permissions [Opens in a new window]

Summary

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

There is a high demand for developing effective controllers to perform fast and accurate operations for either flexible link manipulators (FLMs) or rigid link manipulators (RLMs). Thus, this paper is beneficial for such vast field, and it is also advantageous and indispensable for researchers who are interested in robotics to have sufficient knowledge about various controllers of FLMs and RLMs as the controllers’ concepts are elaborated in detail. The paper concentrates in critically reviewing classical controllers, intelligent controllers, robust controllers, and hybrid controllers for both FLMs and RLMs. The advantages and disadvantages of the aforementioned control methods are summarized in this paper; it also has a detailed comparison for the controllers in terms of the design difficulty, performance, and the suitability for controlling FLMs or RLMs.

Keywords

Control techniquesFlexible link manipulatorsRigid link manipulators
Type
Articles
Information
Robotica , Volume 38 , Issue 12 , December 2020 , pp. 2239 - 2265
Copyright
Copyright © The Author(s) 2020. Published by Cambridge University Press

References

Xiao, B., Yin, S. and Kaynak, O., “Tracking control of robotic manipulators with uncertain kinematics and dynamics,” IEEE Trans. Ind. Electron. 63(10), 6439–6449 (2016).CrossRefGoogle Scholar
Mondal, S. and Mahanta, C., “Adaptive second order terminal sliding mode controller for robotic manipulators,” J. Franklin Inst. 351(4), 2356–2377 (2014).CrossRefGoogle Scholar
Alandoli, E., Sulaiman, M. and Rashid, M., “A review study on flexible link manipulators,” J. Telecommun. Electron. Comput. Eng. Fig. 8(2), 93–97 (2016).Google Scholar
Sun, C., Gao, H., He, W. and Yu, Y., “Fuzzy neural network control of a flexible robotic manipulator using assumed mode method,” IEEE Trans. Neural Networks Learn. Syst. 29(11), 5214–5227 (2018).CrossRefGoogle ScholarPubMed
Mejerbi, M., Zribi, S. and Knani, J., “Dynamic Modeling of Flexible Manipulator Based on a Large Number of Finite Elements,” IEEE International Conference on Advanced Systems and Electric Technologies (2018) pp. 357–362.Google Scholar
Tavasoli, A. and Mohammadpour, O., “Dynamic modeling and adaptive robust boundary control of a flexible robotic arm with 2-dimensional rigid body rotation,” Int. J. Adapt. Control Signal Process. 32(6), 891–907 (2018).CrossRefGoogle Scholar
Shitole, C. and Sumathi, P., “Sliding DFT-based vibration mode estimator for single-link flexible manipulator,” IEEE/ASME Trans. Mechatron. 20(6), 3249–3256 (2015).CrossRefGoogle Scholar
Wang, F. Y. and Gao, Y., “On frequency sensitivity and mode orthogonality of flexible robotic manipulators,” IEEE/CAA J. Autom. Sin. 3(4), 394–397 (2016).Google Scholar
He, W., Ouyang, Y. and Hong, J., “Vibration control of a flexible robotic manipulator in the presence of input deadzone,” IEEE Trans. Ind. Inf. 13(1), 48–59 (2017).CrossRefGoogle Scholar
Shawky, A., Zydek, D., Elhalwagy, Y. Z. and Ordys, A., “Modeling and nonlinear control of a flexible-link manipulator,” Appl. Math. Model. 37(23), 9591–9602 (2013).CrossRefGoogle Scholar
Suklabaidya, S., Lochan, K. and Roy, B. K., “Control of Rotational Base Single Link Flexible Manipulator Using Different SMC Techniques for Variable Payloads,” IEEE International Conference on Energy, Power and Environment: Towards Sustainable Growth, ICEPE, Shillong, India (2015) pp. 1–6.Google Scholar
San-Millan, A., Feliu, V. and Garcia, A., “A Two-Stage Control Scheme Of Single-Link Flexible Manipulators,” Proceedings of the IEEE 23rd Mediterranean Conference on Control and Automation, MED (2015) pp. 1098–1105.Google Scholar
Neugschwandtner, G., Reekmans, M. and Van Der Linden, D., “An Open Automation Architecture for Flexible Manufacturing,” IEEE 18th Conference on Emerging Technologies & Factory Automation (2013) pp. 1–5.Google Scholar
Akyüz, I. H., Kizir, S. and Bingül, Z., “Fuzzy Logic Control of Single-Link Flexible Joint Manipulator,” Proceedings of the IEEE International Conference on Industrial Technology (2011) pp. 306–311.Google Scholar
Raouf, F., Mohamad, S. and Maarouf, S., “Distributed control strategy for flexible link manipulators,” Robotica 33(04), 768–786 (2015).Google Scholar
Dixit, R. and Kumar, R. P., “Working and limitations of cable stiffening in flexible link manipulators,” Adv. Acoust. Vib. 2016, 1–9 (2016). doi:10.1155/2016/4503696.Google Scholar
Ding, W. and Shen, Y., “Analysis of Transient Deformation Response for Flexible Robotic Manipulator Using Assumed Mode Method,” IEEE 2nd Asia-Pacific Conference on Intelligent Robot Systems, ACIRS (2017) pp. 331–335.Google Scholar
Khairudin, M., “Dynamic modelling of a flexible link manipulator robot using AMM,” Telkomnika Indones. J. Electr. Eng. 6(3), 187–192 (2010).Google Scholar
Akyuz, I. H., Yolacan, E., Ertunc, H. M. and Bingul, Z., “PID and State Feedback Control of a Single-Link Flexible Joint Robot Manipulator,” IEEE International Conference on Mechatronics (2011) pp. 409–414.Google Scholar
Ho, M. T. and Tu, Y. W., “PID Controller Design for a Flexible-Link Manipulator,” Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference (2005) pp. 6841–6846.Google Scholar
Ang, K. H., Chong, G. and Li, Y., “PID control system analysis, design, and technology,” IEEE Trans. Control Syst. Technol. 13(4), 559–576 (2005).Google Scholar
Pedro, J. O. and Tshabalala, T., “Hybrid NNMPC/PID Control of a Two-Link Flexible Manipulator with Actuator Dynamics,” 10th Asian Control Conference: Emerging Control Techniques for a Sustainable. World, ASCC 2015 (2015).CrossRefGoogle Scholar
Mahamood, R. M. and Pedro, J. O., “Hybrid PD/PID Controller Design for Two-Link Flexible Manipulators,” Proceedings of the IEEE 8th Asian Control Conference (2011) pp. 1358–1363.Google Scholar
Annisa, J., Darus, I. M., Tokhi, M. and Mohamaddan, S., “Implementation of PID based controller tuned by Evolutionary Algorithm for Double Link Flexible Robotic Manipulator,” IEEE International Conference on Computational Approach in Smart Systems Design and Applications (2018) pp. 1–5.Google Scholar
Tijani, I. B., Akmeliawati, R., Muthalif, A. G. A. and Legowo, A., “Optimization of PID Controller for Flexible Link System Using a Pareto-Based Multi-Objective Differential (PMODE) Evolution,” IEEE 4th International Conference on Mechatronics Integrated Engineering for Industrial and Societal Development, ICOM (2011) pp. 17–19.Google Scholar
Kumar, E. V., Jerome, J. and Srikanth, K., “Algebraic Approach for Selecting the Weighting Matrices of Linear Quadratic Regulator,” Proceeding IEEE International Conference on Green Computing, Communication and Electrical Engineering (2014) pp. 1–6.Google Scholar
Khairudin, M., Mohamed, Z. and Husain, A. R., “Dynamic model and robust control of flexible link robot manipulator,” Telkomnika 9(2), 279–286 (2011).CrossRefGoogle Scholar
Alandoli, E. A., Rashid, M. Z. A. and Sulaiman, M., “A comparison of PID and LQR controllers for position tracking and vibration suppression of flexible link manipulator,” J. Theor. Appl. Inf. Technol. 95(13), 2949–2955 (2017).Google Scholar
Ahmad, M. A., “Vibration and Input Tracking Control of Flexible Manipulator Using LQR with Non-Collocated PID CONTRoller,” UKSIM European Symposium on Computer Modeling and Simulation (2008) pp. 40–45.Google Scholar
Ahmad, M. A. and Mohamed, Z., “Techniques of Vibration and End-Point Trajectory Control of Flexible Manipulator,” 6th International Symposium on Mechatronics and its Applications, ISMA (2009) pp. 1–6.Google Scholar
Baroudi, M., Saad, M. and Ghie, W., “State-Feedback and Linear Quadratic Regulator Applied to a Single Link Flexible Manipulator.pdf,” Proceedings of the IEEE International Conference on Robotics and Biomimetics, vol. 2 (2009) pp. 1381–1386.Google Scholar
Saini, S. C., Sharma, Y., Bhandari, M. and Satija, U., “Comparison of Pole Placement and LQR Applied to Single Link Flexible Manipulator,” Proceedings - International Conference on Communication Systems and Network Technologies, CSNT 2012 (2012) pp. 843–847.Google Scholar
Solihin, M. I., Wahyudi, A. Legowo and Akmeliawati, R., “Comparison of LQR and PSO-Based State Feedback Controller for Tracking Control of a Flexible Link Manipulator,” 2nd IEEE International Conference on Information Management and Engineering (2010) pp. 354–358.Google Scholar
Lu, E., Li, W., Yang, X., Fan, M. and Liu, Y., “Modelling and composite control of single flexible manipulators with piezoelectric actuators,” Shock Vib., 2016, 1–14 (2016). doi:10.1155/2016/2689178.CrossRefGoogle Scholar
Kumar, R. and Kumar, M., “Improvement Power System Stability Using Unified Power Flow Controller based on hybrid Fuzzy Logic-PID TUNing in SMIB SYStem,” Proceedings of the International Conference on Green Computing and Internet of Things, ICGCIoT (2015) pp. 815–819.Google Scholar
Bingül, Z. and Karahan, O., “A fuzzy logic controller tuned with PSO for 2 DOF robot trajectory control,” Expert Syst. Appl. 38(1), 1017–1031 (2011).CrossRefGoogle Scholar
Singh, A. and Londhe, P. S., “Design of Signed Distance Method Based Fuzzy Logic Controller for TITO Process,” Recent Developments in Control, Automation & Power Engineering, RDCAPE 2017 (2017) pp. 13–17.Google Scholar
Mbede, J. B., Huang, X. and Wang, M., “Robust neuro-fuzzy sensor-based motion control among dynamic obstacles for robot manipulators,” IEEE Trans. Fuzzy Syst. 11(2), 249–261 (2003).CrossRefGoogle Scholar
Rahimi, H. N. and Nazemizadeh, M., “Dynamic analysis and intelligent control techniques for flexible manipulators: A review,” Adv. Robot. 28(2), 63–76 (2014).CrossRefGoogle Scholar
Botsali, F. M., Kalyoncu, M., Tinkir, M. and Önen, Ü., “Fuzzy Logic Trajectory Control of Flexible Robot Manipulator with Rotating Prismatic Joint,” 2nd IEEE International Conference on Computer and Automation Engineering, ICCAE, vol. 3 (2010) pp. 35–39.Google Scholar
Dehghanil, A. and Khodadadi, H., “Fuzzy Logic Self-Tuning PID Control for a Single-Link Flexible Joint Robot Manipulator in the presence of Uncertainty,” IEEE 15th International Conference on Control, Automation and Systems (ICCAS) (2015) pp. 186–191.Google Scholar
Cao, Q. and Yu, A., “Optimal Actuator Placement for Vibration Control of Two-Link Piezoelectric Flexible Manipulator,” IEEE International Conference on Mechanic Automation and Control Engineering (2010) pp. 2448–2451.Google Scholar
Ahmad, M. A., Raja Ismail, R. M. T., Ramli, M. S., Zawawi, M. A., Hambali, N. and Abd Ghani, N. M., “Vibration Control of Flexible Joint Manipulator Using Input Shaping with PD-Type Fuzzy Logic Control,” IEEE International Symposium on Industrial Electronics (2009) pp. 1184–1189.Google Scholar
Ahmad, M. A., Raja Ismail, R. M. T., Ramli, M. S., Zawawi, M. A. and Suid, M. H., “Vibration control strategy for flexible joint manipulator: A fuzzy logic control approach,” IEEE Symposium on Industrial Electronics and Applications (2010) pp. 469–474.Google Scholar
Li, Y., Tong, S. and Li, T., “Adaptive fuzzy output-feedback control for a single-link flexible robot manipulator driven DC motor,” Nonlinear Anal. Real World Appl. 14(1), 483–494 (2013).CrossRefGoogle Scholar
Tian, L. and Collins, C., “Adaptive neuro-fuzzy control of a flexible manipulator,” Mechatronics 15(10), 1305–1320 (2005).CrossRefGoogle Scholar
Ahmad, M. A., Nasir, A. N. K., Hambali, N. and Ishak, H., “Vibration and Input Tracking Control of Flexible Manipulator Using Hybrid Fuzzy Logic Controller,” Proc. IEEE Int. Conf. Mechatronics Autom. ICMA (2008) pp. 593–598.Google Scholar
Kasdirin, H. A., Assemgul, M., and Tokhi, M. O., “Fuzzy Logic Based Controller for a Single-Link Flexible Manipulator Using Modified Invasive Weed Optimization,” IEEE International Conference on Evolving and Adaptive Intelligent. Systems EAIS, Douai, France (2015) pp. 1–6.Google Scholar
Khorasgani, H. G., Ghiasi, N. E., Farshad, A. and Talebi, H. A., “Nonlinear Robust Control of Flexible-Link Manipulator with Fuzzy Compensator: Experimental RESUlts,” 2nd International Conference on Control, Instrumentation and Automation, ICCIA (2012) pp. 993–998.Google Scholar
Shi, J., Zheng, W., Li, J., and Chen, D., “A Distributed Fuzzy Logic Controller Based Aptitudinal Control For Single-Link Flexible Manipulator,” IEEE Symposium on Electrical & Electronics Engineering (EEESYM), Kuala Lumpur, Malaysia (2012) pp. 2–4.Google Scholar
Kiang, C. T., Spowage, A. and Yoong, C. K., “Review of control and sensor system of flexible manipulator,” J. Intell. Robot. Syst. Theory Appl. 77, 187–213 (2015). doi:10.1007/s10846-014-0071-4.CrossRefGoogle Scholar
Zhang, H., Qin, C. and Luo, Y., “Neural-network-based constrained optimal control scheme for discrete-time switched nonlinear system using dual heuristic programming,” IEEE Trans. Autom. Sci. Eng. 11(3), 839–849 (2014).CrossRefGoogle Scholar
Model, S., Sun, C., He, W., Member, S., Hong, J. and Member, S., “Neural network control of a flexible robotic manipulator using the lumped,” IEEE Trans. Syst. MAN Cybern. Syst. 47(8), 1863–1874 (2017).Google Scholar
Gao, H., He, W., Zhou, C. and Sun, C., “Neural network control of a two-link flexible robotic manipulator using assumed mode method,” IEEE Trans. Ind. Inf. 15(2), 755–765 (2018).CrossRefGoogle Scholar
Xu, B., “Composite learning control of flexible-link manipulator using NN and DOB,” IEEE Trans. Syst. Man, Cybern. Syst. 48(11), 1979–1985 (2018).CrossRefGoogle Scholar
Maouche, A. R. and Meddahi, H., “A fast adaptive artificial neural network controller for flexible link manipulators,” Int. J. Adv. Comput. Sci. Appl. 7(1), 298–308 (2016).Google Scholar
Su, Z. and Khorasani, K., “A neural-network-based controller for a single-link flexible manipulator using the inverse dynamics approach,” IEEE Trans. Ind. Electron. 48(6), 1074–1086 (2001).Google Scholar
Subudhi, B. and Morris, A. S., “Singular perturbation based neuro-H8 control scheme for a manipulator with flexible links and joints,” Robotica 24(2), 151–161 (2006).CrossRefGoogle Scholar
Neto, A. D. A., Goes, L. C. S. and Ucio Nascimento, J. C. L., “Accumulative learning using multiple ANN for flexible link control,” EEE Trans. Aerosp. Electron. Syst. 46(2), 508–524 (2010).Google Scholar
Tang, Y., Sun, F. and Sun, Z., “Neural network control of flexible-link manipulators using sliding mode,” Neurocomputing 70(1–3), 288–295 (2006).CrossRefGoogle Scholar
Rahmani, B. and Belkheiri, M., “Adaptive neural network output feedback control for flexible multi-link robotic manipulators,” Int. J. Control 92(10), 1–15 (2018).Google Scholar
Jiang, Y., Yin, S. and Kaynak, O., “Data-driven monitoring and safety control of industrial cyber-physical systems: basics and beyond,” IEEE Access 6, 47374–47384 (2018).CrossRefGoogle Scholar
Yang, L. and Yang, J., “Nonsingular fast terminal sliding-mode control for nonlinear dynamical systems,” Int. J. Robust Nonlinear Control 21(16), 1865–1879 (2011).CrossRefGoogle Scholar
Soon, C. C., PSO-Tuned PID Sliding Surface of Sliding Mode Control for an Electro-Hydraulic Actuator System Master Thesis (Universiti Teknikal Malaysia Melaka, 2017).Google Scholar
Wang, Y., Wang, C., Lu, P. and Wang, Y., “High-Order Nonsingular Terminal Sliding Mode Optimal Control of Two-Link Flexible Manipulators,” Annual Conference of the IEEE Industrial Electronics Society (2011) pp. 3953–3958.Google Scholar
Kherraz, K., Hamerlain, M. and Achour, N., “Robust Sliding Mode Controller for a Class of Under-Actuated Systems,” 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, Hammamet, Tunisia (2014) pp. 942–946.Google Scholar
Kurode, S. and Dixit, P., “Output Feedback Control of Flexible Link Manipulator Using Sliding Modes,” 7th International Conference on Electrical and Computer Engineering, Dhaka, Bangladesh (2012) pp. 949–952.Google Scholar
Delavari, H., Lanusse, P. and Sabatier, J., “Fractional order controller design for a flexible link manipulator robot,” Asian J. Control 15(3), 783–795 (2013).CrossRefGoogle Scholar
Hisseine, D. and Lohmann, B., “Robust Control for a Flexible-Link Manipulator Using Sliding Mode Techniques and Nonlinear H∞ Control Design Methods,” IEEE International Conference on Robotics and Automation, Seoul, Korea (2001) pp. 3865–3870.Google Scholar
Gadsden, S. A. and Alshabi, M., “A Comparison of Vibration Control Strategies for a Flexible-Link Robot Arm,” 10th International Symposium on Mechatronics and its Applications (2015) pp. 1–5.Google Scholar
Rsetam, K., Cao, Z. and Man, P. Z., “Hierarchical Sliding Mode Control Applied to a Single-Link Flexible Joint Robot Manipulator,” International Conference on Advanced Mechatronic Systems, Melbourne, Australia (2016) pp. 476–481.Google Scholar
Rsetam, K., Cao, Z. and Man, P. Z., “Hierarchical Non-Singular Terminal Sliding Mode Controller for a Single Link Flexible Joint Robot Manipulator,” IEEE 56th Annual Conference on Decision and Control (CDC), Melbourne, Australia (2017) pp. 6677–6682.Google Scholar
Arisoy, A., Bayrakceken, M. K., Basturk, S., Gokasan, M. and Bogosyan, O. S., “High Order Sliding Mode Control of a Space Robot Manipulator,” 5th International Conference on Recent Advances in Space Technologies, Istanbul, Turkey (2011) pp. 833–838.Google Scholar
Duarte, F. and Bohn, C., “Partially Decentralized Sliding Mode Control of Two Flexible-link Robots to Reduce Transient Responses,” IEEE 20Th International Conference on System Theory, Control and Computing (ICSTCC), Sinaia, Romania (2016) pp. 369–374.Google Scholar
Han, L., Chen, M., Wu, Q. and Li, X., “Sliding Mode Control Using Disturbance Observer for a Flexible Link Robot,” 14th IEEE International Workshop on Variable Structure Systems, Nanjing, China (2016) pp. 448–453.Google Scholar
Rsetam, K., Cao, Z., Man, Z. and Mitrevska, M., “Optimal Second Order Integral Sliding Mode Control for a Flexible Joint Robot Manipulator,” 43rd Annual Conference of the IEEE Industrial Electronics Society, Beijing, China (2017) pp. 3069–3074.Google Scholar
Rsetam, K., Cao, Z. and Man, Z., “Super-Twisting Based Integral Sliding Mode Control Applied to a Rotary Flexible Joint Robot Manipulator,” 11th Asian Control Conference, ASCC, Australia (2018) pp. 2905–2910.Google Scholar
Utkin, V. and Lee, H., “Chattering Problem in Sliding Mode Control Systems,” International Workshop on Variable Structure Systems, Alghero, Italy (2006) pp. 346–350.Google Scholar
Lochan, K., Suklabaidya, S. and Roy, B. K., “Comparison of Chattering In Single Link Flexible Manipulator with Sliding Mode Controllers,” International Conference on Energy, Power and Environment: Towards Sustainable Growth, ICEPE, Shillong, India (2015) pp. 1–6.Google Scholar
Zeinali, M., “First-Order Continuous Adaptive Sliding Mode Control for Robot Manipulators with Finite-Time Convergence of Trajectories to Real Sliding Mode,” 15th International Workshop on Variable Structure Systems (VSS), Graz, Austria (2018) pp. 261–266.Google Scholar
Yanmin, W., Yuqing, C. A. O. and Hongwei, X. I. A., “Optimized Continuous Non-singular Terminal Sliding Mode Control of Uncertain Flexible Manipulators,” 34th Chinese Control Conference (CCC), Hangzhou, China (2015) pp. 3392–3397.Google Scholar
Si, Y., Pu, J. and Sun, L., “A Fast Terminal Sliding Mode Control of Two-Link Flexible Manipulators for Trajectory Tracking,” Chinese Automation Congress, CAC, Jinan, China (2017) pp. 6387–6391.Google Scholar
Mujumdar, A., Tamhane, B. and Kurode, S., “Fractional Order Modeling and Control of a Flexible Manipulator Using Sliding Modes,” The American Control Conference, Portland, Oregon, USA (2014) pp. 2011–2016.Google Scholar
Mujumdar, A., Kurode, S. and Tamhane, B., “Fractional Order Sliding Mode Control for Single Link Flexible Manipulator,” IEEE International Conference on Control Applications, Hyderabad, India (2013) pp. 288–293.Google Scholar
Bansal, A. and Sharma, V., “Design and analysis of robust H-infinity controller,” Control Theory Inf. 3(2), 7–14 (2013).Google Scholar
Shawky, A. M., Ordys, A. W., Petropoulakis, L. and Grimble, M. J., “Position control of flexible manipulator using non-linear H∞ with state-dependent Riccati equation,” Proc. Inst. Mech. Eng. Part I J. Syst. Control Eng. 221(3), 475–486 (2007).Google Scholar
Jodouin, P., Saad, M. and Wamkeue, R., “Control of a Flexible Arm System: Comparison of H∞ and Loop Transfer Recover Methods-Application to An Experimental Arm,” 17th IEEE Mediterranean Electrotechnical Conference, Beirut, Lebanon (2014) pp. 310–314.Google Scholar
Altıner, B., Delibas, A. and Erol, B., “Modeling and control of flexible link manipulators for unmodeled dynamics effect,” Proc. IMechE Part Inst. J. Syst. Control Eng., 233(3), 245–263 (2018).CrossRefGoogle Scholar
Axelsson, P., Helmersson, A. and Norrlöf, M., “H∞ Controller Design Methods Applied to One Joint of a Flexible Industrial Manipulator,” World Congress The International Federation of Automatic Control, Cape Town, South Africa (2014) pp. 210–216.Google Scholar
Hu, J., Bohn, C. and Wu, H. R., “Systematic H∞ weighting function selection and its application to the real-time control of a vertical take-off aircraft,” Control Eng. Pract. 8(3), 241–252 (2000).CrossRefGoogle Scholar
Sayahkarajy, M., Mohamed, Z., Faudzi, A. A. M. and Supriyanto, E., “Hybrid vibration and rest-to-rest control of a two-link flexible robotic arm using H∞ loop-shaping control design,” Eng. Comput. 33(2), 395–409 (2016).CrossRefGoogle Scholar
Duarte, F., Ballesteros, P. and Bohn, C., “H-infinity and State-feedback Controllers for Vibration Suppression in a Single-link Flexible Robot,” IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Wollongong, Australia (2013) pp. 1719–1724.Google Scholar
Orszulik, R. R. and Shan, J., “Active vibration control using genetic algorithm-based system identification and positive position feedback,” Smart Mater. Struct. 21(5), 1–10 (2012).Google Scholar
Alandoli, E. A., Shah, H. N. M., Sulaiman, M., Rashid, M. Z. A. and Aras, M. S. M., “PD/H-8 integrated controller for position tracking and vibration suppression of flexible link manipulator system,” Int. J. Mech. Mechatronics Eng. IJMME-IJENS 18(03), 54–61 (2018).Google Scholar
Sayahkarajy, M. and Mohamed, Z., “Mixed sensitivity H2/H-8 control of a flexible-link robotic arm,” Int. J. Mech. Mechatronics Eng. 14(1), 21–27 (2014).Google Scholar
Yuan, Y., Fuchun, S. U. N., Huaping, L. I. U. and Qinyi, W., “Multi-objective Robust Control of Flexible-link Manipulators Based on Fuzzy Singularly Perturbed Model with Multiple Perturbation Parameters,” the 31st Chinese Control Conference, Hefei, China (2012) pp. 2613–2617.Google Scholar
Makarov, M., Grossard, M., Rodríguez-Ayerbe, P. and Dumur, D., “Modeling and preview h8 control design for motion control of elastic-joint robots with uncertainties,” IEEE Trans. Ind. Electron. 63(10), 6429–6438 (2016).CrossRefGoogle Scholar
Wang, X. and Chen, D., “Output tracking control of a one-link flexible manipulator via causal inversion,” IEEE Trans. Control Syst. Technol. 14(1), 141–148 (2006).CrossRefGoogle Scholar
Wang, F. and Liu, X. P., “H infinity control of flexible joint robot via T-S fuzzy model,” Appl. Mech. Mater. 128–129, 894–897, 2011.CrossRefGoogle Scholar
Ho, M.-T. and Tu, Y.-W., “Position control of a single-link flexible manipulator using H∞-based PID control,” IEE Proc. Control Theory Appl. 153(5), 615–622 (2006).CrossRefGoogle Scholar
Atashzar, S. F., Talebi, H. A., Yazdanpanah, M. J. and Towhidkhah, F., “Tip Position Tracking of Flexible-Link Manipulators Based on Online Robust Trajectory Modification,” 36th Annual Conference of the IEEE Industrial Electronics Society (2010) pp. 1651–1656.Google Scholar
Hu, J. and Xu, G., “Vibration control of piezoelectric flexible structure using robust control methodology,” J. Theor. Appl. Inf. Technol. 51(2), 264–274 (2013).Google Scholar
Wang, Y., Han, F., Feng, Y. and Xia, H., “Hybrid Continuous Nonsingular Terminal Sliding Mode Control of Uncertain Flexible Manipulators,” Annual Conference of the IEEE Industrial Electronics Society (2014) pp. 190–196.Google Scholar
Maouche, A. R. and Attari, M., “Nonlinear Adaptive RBFNN Control of a One-Link Flexible Manipulator,” International Conference on Web Intelligence (2010) pp. 165–170.Google Scholar
Njeri, W., Sasaki, M. and Matsushita, K., “Two-Degree-of-Freedom Control of a Multilink Flexible Manipulator Using Filtered Inverse Feedforward Controller and Strain Feedback Controller,” Proceedings of the 2017 IEEE International Conference on Applied System Innovation, Meen, Prior Lam (2018) pp. 972–975.Google Scholar
Xu, B. and Zhang, P., “Composite learning sliding mode control of flexible-link manipulator,” Complexity 2017, 1–6 (2017). doi:10.1155/2017/9430259.CrossRefGoogle Scholar
Yang, C., Xu, Y., Zhou, L. and Sun, Y., “Model-free composite control of flexible manipulators based on adaptive dynamic programming,” Complexity 2018, 1–9 (2018). doi:10.1155/2018/9720309.CrossRefGoogle Scholar
Alam, M. S. and Tokhi, M. O., “Hybrid fuzzy logic control with genetic optimisation for a single-link flexible manipulator,” Eng. Appl. Artif. Intell. 21(6), 858–873 (2008).CrossRefGoogle Scholar
Zhang, Y., Yang, T. and Sun, Z., “Neuro-sliding-mode control of flexible-link manipulators based on singularly perturbed model,” Tsinghua Sci. Technol. 14(4), 444–451 (2009).CrossRefGoogle Scholar
Abdullahi, A. M., Mohamed, Z., Muhammad, M. and Bature, A. A., “Vibration and tip deflection control of a single-link flexible manipulator,” Int. J. Instrum. Control Syst. 3(4), 17–27 (2013).Google Scholar
Mirshekaran, M., Piltan, F., Esmaeili, Z., Khajeaian, T. and Kazeminasa, M., “Design sliding mode modified fuzzy linear controller with application to flexible robot manipulator,” Int. J. Mod. Educ. Comput. Sci. 5(10), 53–63 (2013).CrossRefGoogle Scholar
Dubay, R., Hassan, M., Li, C. and Charest, M., “Finite element based model predictive control for active vibration suppression of a one-link flexible manipulator,” ISA Trans. 53(5), 1609–1619 (2014).CrossRefGoogle ScholarPubMed
Malzahn, J., Ruderman, M., Phung, A. S., Hoffmann, F. and Bertram, T., “Input Shaping and Strain Gauge Feedback Vibration Control of An Elastic Robotic Arm,” Conference on Control and Fault-Tolerant Systems, Nice, France (2010) pp. 672–677.Google Scholar
Malzahn, J., Phung, A. S., Hoffmann, F. and Bertram, T., “Vibration Control of a Multi-Flexible-Link Robot Arm Under Gravity,” IEEE International Conference on Robotics and Biomimetics, ROBIO, Phuket, Thailand (2011) pp. 1249–1254.Google Scholar
Tumari, M. Z. M., Ahmad, M. A., Saealal, M. S., Zawawi, M. A., Mohamed, Z. and Yusop, N. M., “The Direct Strain Feedback with PID Control Approach for a Flexible Manipulator: Experimental Results,” 11th International Conference on Control, Automation and Systems, Gyeonggi-do, Korea (2011) pp. 7–12.Google Scholar
Wang, Y., Xia, H. and Wang, C., “Hybrid Controllers for Two-Link Flexible Manipulators,” International Conference on Applied Informatics and Communication, Xi’an, China (2011) pp. 409–418.Google Scholar
Hussain, S. A. and Kadri, M. B., “Control of Under-Actuated Two-Link ROBOT with Hybrid LQ-Fuzzy Controller,” International Conference on Robotics and Emerging Allied Technologies in Engineering (iCREATE), Islamabad, Pakistan (2014) pp. 174–179.Google Scholar
Islam, S. and Liu, P. X., “PD output feedback control design for industrial robotic manipulators,” IEEE/ASME Trans. Mechatron. 16(1), 187–197 (2011).CrossRefGoogle Scholar
Hussein, M. T. and Nemah, M. N., “Control of a Two-link (Rigid-Flexible) Manipulator,” the 3rd RSI International Conference on Robotics and Mechatronics, Tehran, Iran (2015) pp. 720–724.Google Scholar
Reyhanoglu, M., Hoffman, D. and De Wit, J., “Nonlinear Modeling and Control of a Two-Link Hybrid Manipulator,” 14th International Conference on Control, Automation, Robotics and Vision, Phuket, Thailand (2016) pp. 1–5.Google Scholar
Hultmann Ayala, H. V. and Dos Santos Coelho, L., “Tuning of PID controller based on a multiobjective genetic algorithm applied to a robotic manipulator,” Expert Syst. Appl. 3910), 8968–8974 (2012).CrossRefGoogle Scholar
Santibañez, V., Camarillo, K., Moreno-Valenzuela, J. and Campa, R., “A practical PID regulator with bounded torques for robot manipulators,” Int. J. Control. Autom. Syst. 8(3), 544–555 (2010).CrossRefGoogle Scholar
Yarza, A., Santibanez, V. and Moreno-Valenzuela, J., “Global asymptotic stability of the classical PID controller by considering saturation effects in industrial robots,” Int. J. Adv. Robot. Syst. 8(4), 34–42 (2011).CrossRefGoogle Scholar
Bingül, Z. and Karahan, Ŏguzhan, “Fractional PID controllers tuned by evolutionary algorithms for robot trajectory control,” Turkish J. Electr. Eng. Comput. Sci. 20(SUPPL.1), 1123–1136 (2012).Google Scholar
Sharma, R., Gaur, P. and Mittal, A. P., “Performance analysis of two-degree of freedom fractional order PID controllers for robotic manipulator with payload,” ISA Trans. 58, 279–291 (2015). doi:10.1016/j.isatra.2015.03.013.CrossRefGoogle ScholarPubMed
Dumlu, A. and Erenturk, K., “Trajectory tracking control for a 3-DOF parallel manipulator using fractional-order PID control,” IEEE Trans. Ind. Electron. 61(7), 3417–3426 (2014).CrossRefGoogle Scholar
Li, X. and Yu, W., “A Systematic Tunning Method of PID Controller for Robot Manipulators,” IEEE International Conference on Control and Automation, ICCA, Santiago, Chile (2011) pp. 274–279.Google Scholar
Ahmad, S. G. and Elbanna, A. S., “Dynamic modelling with a modified PID controller of a three link rigid dynamic modelling with a modified PID controller of a three link rigid manipulator,” Int. J. Comput. Appl. 179(34), 37–42 (2018).Google Scholar
Al-Qahtani, H. M., Mohammed, A. A. and Sunar, M., “Dynamics and control of a robotic arm having four links,” Arab. J. Sci. Eng. 42(5), 1841–1852 (2017).CrossRefGoogle Scholar
Leines, M. T. and Yang, J. S., “LQR Control of An Under Actuated Planar Biped Robot,” 6th IEEE Conference on Industrial Electronics and Apllications, Beijing, China (2011) pp. 1684–1689.Google Scholar
Ajwad, S. A., Iqbal, J., Islam, R. U., Alsheikhy, A., Almeshal, A. and Mehmood, A., “Optimal and robust control of multi DOF robotic manipulator: Design and hardware realization,” Cybern. Syst. 49(1), 77–93 (2018).CrossRefGoogle Scholar
Van Den Berg, J., Abbee, P. and Goldberg, K., “LQG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information,” Int. J. Rob. Res. 30(7), 895–913 (2011).CrossRefGoogle Scholar
Meza, J. L., Santibáñez, V., Soto, R. and Llama, M. A., “Fuzzy self-tuning PID semiglobal regulator for robot manipulators,” IEEE Trans. Ind. Electron. 59(6), 2709–2717 (2012).CrossRefGoogle Scholar
Amer, A. F., Sallam, E. A. and Elawady, W. M., “Fuzzy Pre-Compensated Fuzzy Self-Tuning Fuzzy PID Controller of 3 DOF Planar Robot Manipulators,” IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Montréal, Canada (2010) pp. 599–604.Google Scholar
Biglarbegian, M., Melek, W. W. and Mendel, J. M., “Design of novel interval type-2 fuzzy controllers for modular and reconfigurable robots: Theory and experiments,” IEEE Trans. Ind. Electron. 58(4), 1371–1384 (2011).CrossRefGoogle Scholar
Jamwal, P. K., Xie, S. Q., Tsoi, Y. H. and Aw, K. C., “Forward kinematics modelling of a parallel ankle rehabilitation robot using modified fuzzy inference,” Mech. Mach. Theory 45(11), 1537–1554 (2010).CrossRefGoogle Scholar
Soltanpour, M. R., Khooban, M. H. and Otadolajam, P., “Robust control strategy for electrically driven robot manipulators: adaptive fuzzy sliding mode,” IET Sci. Meas. Technol. 9(3), 322–334 (2015).CrossRefGoogle Scholar
Xia, Q. X., Yu, Y. Q. and Liu, Q. B., “Fuzzy control for underactuated manipulator,” Appl. Mech. Mater. 397–400, 1490–1493 (2013).CrossRefGoogle Scholar
He, W., David, A. O., Yin, Z. and Sun, C., “Neural network control of a robotic manipulator with input deadzone and output constraint,” IEEE Trans. Syst. Man, Cybern. Syst. 46(6), 759–770 (2016).CrossRefGoogle Scholar
He, W., Ofosu Amoateng, D., Yang, C. and Gong, D., “Adaptive neural network control of a robotic manipulator with unknown backlash-like hysteresis,” IET Control Theory Appl. 11(4), 567–575 (2017).CrossRefGoogle Scholar
He, W., Chen, Y. and Yin, Z., “adaptive neural network control of an uncertain robot with full-state constraints,” IEEE Trans. Cybern. 46(3), 620–629 (2016).CrossRefGoogle ScholarPubMed
He, W., Dong, Y. and Sun, C., “Adaptive neural impedance control of a robotic manipulator with input saturation,” IEEE Trans. Syst. Man Cybern. Syst. 46(3), 334–344, 2016.CrossRefGoogle Scholar
Li, Y., Ge, S. S., Zhang, Q. and Lee, T. H., “Neural networks impedance control of robots interacting with environments,” IET Control Theory Appl. 7(11), 1509–1519 (2013).CrossRefGoogle Scholar
Puga-Guzmán, S., Moreno-Valenzuela, J. and Santibáñez, V., “Adaptive neural network motion control of manipulators with experimental evaluations,” Sci. World J. 2014, 1–3 (2014). doi:10.1155/2014/694706.CrossRefGoogle ScholarPubMed
Kumar, N., Panwar, V., Sukavanam, N., Sharma, S. P. and Borm, J. H., “Neural network based hybrid force/position control for robot manipulators,” Int. J. Precis. Eng. Manuf. 12(3), 419–426 (2011).CrossRefGoogle Scholar
Singh, H. P. and Sukavanam, N., “Stability analysis of robust adaptive hybrid position/force controller for robot manipulators using neural network with uncertainties,” Neural Comput. Appl. 22(7–8), 1745–1755 (2013).CrossRefGoogle Scholar
Liu, H. and Zhang, T., “Adaptive neural network finite-time control for uncertain robotic manipulators,” J. Intell. Robot. Syst. Theory Appl. 75(3–4), 363–377 (2014).CrossRefGoogle Scholar
Sefriti, S., Boumhidi, J., Naoual, R. and Boumhidi, Y., “Adaptive neural network sliding mode control for electrically-driven robot manipulators,” Control Eng. Appl. Inf. 14(4), 27–32 (2012).Google Scholar
Sun, T., Pei, H., Pan, Y., Zhou, H. and Zhang, C., “Neural network-based sliding mode adaptive control for robot manipulators,” Neurocomputing 74(14–15), 2377–2384 (2011).CrossRefGoogle Scholar
Tavoosi, J., Jokandan, A. S. and Daneshwar, M. A., “A new method for position control of a 2-DOF robot arm using neuro-fuzzy controller,” Indian J. Sci. Technol. 5(3), 2253–2257 (2012).Google Scholar
Wai, R.-J., Huang, Y.-C., Shih, C.-Y. and Yang, Z.-W., “Adaptive fuzzy-neural-network velocity sensorless control for robot manipulator position tracking,” IET Control Theory Appl. 4(6), 1079–1093 (2010).CrossRefGoogle Scholar
Zhao, Y. and Cheah, C. C., “Vision-based neural network control for constrained robots with constraint uncertainty,” IET Control Theory Appl. 2(10), 906–916 (2008).CrossRefGoogle Scholar
Islam, S. and Liu, X. P., “Robust sliding mode control for robot manipulators,” IEEE Trans. Ind. Electron. 58(6), 2444–2453 (2011).CrossRefGoogle Scholar
Piltan, F. and Sulaiman, N. B., “Review of sliding mode control of robotic manipulator,” World Appl. Sci. J. 18(12), 1855–1869 (2012).Google Scholar
Capisani, L. M. and Ferrara, A., “Trajectory planning and second-order sliding mode motion/ interaction control for robot manipulators in unknown environments,” IEEE Trans. Ind. Electron. 59(8), 3189–3198 (2012).CrossRefGoogle Scholar
Kuo, T. C., Huang, Y. J. and Hong, B. W., “Design of adaptive sliding mode controller for robotic manipulators tracking control,” Int. J. Comput. Electr. Autom. Control Inf. Eng. 5(5), 453–457 (2011).Google Scholar
Neila, M. B. R. and Tarak, D., “Adaptive terminal sliding mode control for rigid robotic manipulators,” Int. J. Autom. Comput. 8(2), 215–220 (2011).CrossRefGoogle Scholar
Adelhedi, F., Jribi, A., Bouteraa, Y. and Derbel, N., “Adaptive sliding mode control design of a SCARA robot manipulator system under parametric variations,” J. Eng. Sci. Technol. Rev. 8(5), 117–123 (2015).CrossRefGoogle Scholar
Gorji, S. and Yazdanpanah, M. J., “A novel robust adaptive trajectory tracking in robot manipulators,” J. Comput. Robot. 10(2), 1–10 (2017).Google Scholar
Gorji, S. and Yazdanpanah, M. J., “A Robust Adaptive Sliding Mode Controller for Robot Manipulators,” IEEE 7th Conference on Artificial Intelligence and Robotics, IRANOPEN, (2017) pp. 170–176.Google Scholar
Jasim, I. F. and Plapper, P. W., “Adaptive Sliding Mode Control of Switched Constrained Robotic Manipulators,” IEEE International Conference on Industrial Informatics (INDIN) (2013) pp. 305–310.Google Scholar
Baek, J., Jin, M. and Han, S., “A new adaptive sliding-mode control scheme for application to robot manipulators,” IEEE Trans. Ind. Electron. 63(6), 3628–3637 (2016).CrossRefGoogle Scholar
Veysi, M., Soltanpour, M. R. and Khooban, M. H., “A novel self-adaptive modified bat fuzzy sliding mode control of robot manipulator in presence of uncertainties in task space,” Robotica 33(10), 2045–2064 (2015).CrossRefGoogle Scholar
Hwang, J., Kang, Y., Park, J. and Kim, D. W., “Advanced interval type-2 fuzzy sliding mode control for robot manipulator,” Comput. Intell. Neurosci. 2017, 1–11 (2017). doi:10.1155/2017/9640849.CrossRefGoogle ScholarPubMed
Nafia, N., El Kari, A., Ayad, H. and Mjahed, M., “Robust interval type-2 fuzzy sliding mode control design for robot manipulators,” Robotics 7(3), 1–22 (2018).CrossRefGoogle Scholar
Sharkawy, A. B. and Salman, S. A., “An adaptive fuzzy sliding mode control scheme for robotic systems,” Intell. Control Autom. 2(4), 299–309 (2011).CrossRefGoogle Scholar
Jalali, A., Piltan, F., Gavahian, A., Jalali, M. and Adibi, M., “Model-free adaptive fuzzy sliding mode controller optimized by particle swarm for robot manipulator,” Int. J. Inf. Eng. Electron. Business 5(1), 68–78 (2013).Google Scholar
Dumlu, A., “Design of a fractional-order adaptive integral sliding mode controller for the trajectory tracking control of robot manipulators,” Proc. IMechE Part Inst. J. Syst. Control Eng. 232(9), 1–18 (2018).Google Scholar
Zeinali, M. and Notash, L., “Adaptive sliding mode control with uncertainty estimator for robot manipulators,” Mech. Mach. Theory 45(1), 80–90 (2010).CrossRefGoogle Scholar
Ouyang, P. R., Acob, J. and Pano, V., “PD with sliding mode control for trajectory tracking of robotic system,” Robot. Comput. Integr. Manuf. 30(2), 189–200 (2014).CrossRefGoogle Scholar
Rigatos, G., Siano, P. and Raffo, G., “A nonlinear H-infinity control method for multi-DOF robotic manipulators,” Nonlinear Dyn. 88(1), 329–348 (2017).CrossRefGoogle Scholar
Wang, X., Niu, R. S., Chen, C. and Zhao, J., “H infinity switched adaptive control for a class of robot manipulators,” Trans. Inst. Meas. Control 36(3), 347–353 (2014).CrossRefGoogle Scholar
Peng, J., Wang, J. and Wang, Y., “Neural network based robust hybrid control for robotic system: an H∞ approach,” Nonlinear Dyn. 65, 421–431 (2011). doi:10.1007/s11071-010-9902-4.CrossRefGoogle Scholar
Zuo, Y., Wang, Y., Liu, X., Yang, S. X., Huang, L., Wu, X. and Wang, Z., “Neural network robust H infinity tracking control strategy for robot manipulators,” Appl. Math. Model. 34(7), 1823–1838 (2010).CrossRefGoogle Scholar
Panwar, V., “Wavelet neural network-based H∞ trajectory tracking for robot manipulators using fast terminal,” Robotica 35(7), 1488–1503 (2017).CrossRefGoogle Scholar
Chen, Y., Mei, G., Ma, G., Lin, S. and Gao, J., “Robust adaptive inverse dynamics control for uncertain robot manipulator,” Int. J. Innov. Comput. Inf. Control 10(2), 575–587 (2014).Google Scholar
El Hansali Hasnaa, B. M., “Robust Control of Two Link Rigid Manipulator with Nonlinear Dynamic Model,” 3rd International Conference of Electrical and Information Technologies, ICEIT, vol. 5, no. 3 (2017) pp. 3–8.Google Scholar
Yadav, P. S. and Singh, N., “Robust control of two link rigid manipulator,” Int. J. Inf. Electr. Eng. 5(3), 3–8 (2015).Google Scholar
Siqueira, A. A. G., Terra, M. H., Ishihara, J. Y. and Barbeiro, T. L. S., “Underactuated manipulator robot control via H2, H∞, H2/H∞, and μ-synthesis approaches: a comparative study,” J. Braz. Soc. Mech. Sci. Eng. XXXI(4), 279–288 (2009).Google Scholar
Piltan, F., Hosainpour, A., Emamzadeh, S., Nazari, I. and Mirzaie, M., “Design sliding mode controller of with parallel fuzzy inference system compensator to control of robot manipulator,” Int. J. Robot. Autom. 2(4), 149–162 (2013).Google Scholar
Amer, A. F., Sallam, E. A. and Elawady, W. M., “Adaptive fuzzy sliding mode control using supervisory fuzzy control for 3 DOF planar robot manipulators,” Appl. Soft Comput. J. 11(8), 4943–4953 (2011).CrossRefGoogle Scholar
Li, T. S. and Huang, Y., “MIMO adaptive fuzzy terminal sliding-mode controller for robotic manipulators,” Inf. Sci. (Ny). 180(23), 4641–4660 (2010).CrossRefGoogle Scholar
Soltanpour, M. R. and Khooban, M. H., “A particle swarm optimization approach for fuzzy sliding,” Nonlinear Dyn. 74(1–2), 467–478 (2013).CrossRefGoogle Scholar
Piltan, F., Sulaiman, N., Soltani, S., Marhaban, M. H. and Ramli, R., “An Adaptive sliding surface slope adjustment in PD Sliding Mode Fuzzy Control for Robot Manipulator,” Int. J. Control Autom. 4(3), 65–76 (2011).Google Scholar
Zhang, D. and Wei, B., “Design analysis and modelling of a hybrid controller for serial robotic manipulators,” Robotica 35(9), 1888–1905 (2017).CrossRefGoogle Scholar
Sharma, R., Rana, K. P. S. and Kumar, V., “Performance analysis of fractional order fuzzy PID controllers applied to a robotic manipulator,” Expert Syst. Appl. 41(9), 4274–4289 (2014).CrossRefGoogle Scholar
Smith, A. M. C., Yang, C., Ma, H., Culverhouse, P., Cangelosi, A. and Burdet, E., “Novel hybrid adaptive controller for manipulation in complex perturbation environments,” PLoS One, 10(6), 1–19 (2015).Google ScholarPubMed
Rani, K. and Kumar, N., “Design of Intelligent Hybrid Force and Position Control of Robot Manipulator,” 6th International Conference on Smart Computing and Communications, ISCC, Kurukshetra, India (2018) pp. 42–49.Google Scholar
Kapoor, N. and Ohri, J., “Fuzzified PSO-SVM controller for motion control of robotic manipulator,” Int. J. Ind. Syst. Eng. 24(3), 361–383 (2016).Google Scholar
Gierlak, P., Ska, M. M. Ñ. and Ylski, W. Ż., “Neuro-fuzzy control of a robotic manipulator,” Int. J. Appl. Mech. Eng. 19(3), 575–584 (2014).CrossRefGoogle Scholar
Islam, S. and Liu, P. X., “Robust adaptive fuzzy output feedback control system for robot manipulators,” IEEE/ASME Trans. Mechatron. 16(2), 288–296 (2011).CrossRefGoogle Scholar
Mohamed, Z., Khairudin, M., Husain, A. R. and Subudhi, B., “Linear matrix inequality-based robust proportional derivative control of a two-link flexible manipulator,” JVC/J. Vib. Control 22, (5), 1–13 (2016).Google Scholar
Bien, D. X., My, C. A. and Khoi, P. B., “Dynamic modeling and control of a flexible link manipulators with translational and rotational joints,” VNU J. Sci. Math. Phys. 34(1), 52–66 (2018).CrossRefGoogle Scholar
Gamasu, R. and Jasti, V. R. B., “Robust Cohen-Coon PID controller for flexibility of double link manipulator,” Int. J. Control Autom. 7(1), 357–368 (2014).CrossRefGoogle Scholar
Reis, J. C. P. and da Costa, J. S., “Motion planning and actuator specialization in the control of active-flexible link robots,” J. Sound Vib. 331(3255–3270 (2012).CrossRefGoogle Scholar
de Lima, J. J., Tusset, A. M., Janzen, F. C., Piccirillo, V. and Nascimento, C. B., “SDRE applied to position and vibration control of a robot manipulator with a flexible link,” J. Theor. Appl. Mech. 54(4), 1067–1078 (2016).CrossRefGoogle Scholar
Bowkett, J. and Mukherjee, R., “Comparison of Control Methods for Two-Link Planar Flexible Manipulator,” International Design Engineering Technical Conferences and Computers and Information in Engineering Conference IDETC/CIE, Cleveland, Ohio, USA (2017) pp. 1–10.Google Scholar
Akyuz, I. H., Bingul, Z. and Kizir, S., “Cascade fuzzy logic control of a single-link flexible-joint manipulator,” Turk J. Elec. Eng. Comp. Sci. 20(5), 713–726 (2012).Google Scholar
Zirkohi, M. M., Fateh, M. M. and Shoorehdeli, M. A., “Type-2 fuzzy control for a flexible-joint robot using voltage control strategy,” Int. J. Autom. Comput. 10(3), 242–255 (2013).CrossRefGoogle Scholar
Abe, A., “Trajectory planning for flexible Cartesian robot manipulator by using artificial neural network: numerical simulation and experimental verification,” Robotica 29(5), 797–804 (2011).CrossRefGoogle Scholar
Farmanbordar, A. and Hoseini, S. M., “Neural network adaptive output feedback control of flexible link manipulators,” J. Dyn. Syst. Meas. Control 135(2), 1–9 (2013).CrossRefGoogle Scholar
Kurode, S. and Dixit, P., “Sliding mode control of flexible link manipulator using states and disturbance estimation,” Int. J. Adv. Mechatron. Syst. 5(2), 129–137 (2013).CrossRefGoogle Scholar
Peza-Solís, J. F., Silva-Navarro, G. and Castro-Linares, N. R. “Trajectory tracking control in a single flexible-link robot using finite differences and sliding modes,” J. Appl. Res. Technol. 13(1), 70–78 (2015).CrossRefGoogle Scholar
Zulfatman, M. Marzuki, and Mardiyah, N. A., “Two-link flexible manipulator control using sliding mode control based linear matrix inequality,” IOP Conf. Ser. Mater. Sci. Eng. 190(1), 1–9 (2017).CrossRefGoogle Scholar
Lizarraga, I., Etxebarria, V. and Sanz, A., “Sliding-mode adaptive control for flexible- link manipulators using a composite design,” Cybern. Syst. Int. J. 36(5), 471–490 (2005).CrossRefGoogle Scholar
Yun, J. N. and Su, J., “Design of a disturbance observer for a two-link manipulator with flexible joints,” IEEE Trans. Control Syst. Technol. 22(2), 809–815 (2014).CrossRefGoogle Scholar
Zhang, S., Zhang, Y., Zhang, X. and Dong, G., “Fuzzy PID control of a two-link flexible manipulator,” J. Vibroeng. 18(1), 250–266 (2016).Google Scholar
Pradhan, S. K. and Subudhi, B., “Real-time adaptive control of a flexible manipulator using reinforcement learning,” IEEE Trans. Autom. Sci. Eng. 9(2), 237–249 (2012).CrossRefGoogle Scholar
Lochan, K., Roy, B. K. and Subudhi, B., “SMC controlled chaotic trajectory tracking of two-link flexible manipulator with PID sliding surface,” IFAC-PapersOnLine 49(1), 219–224 (2016).CrossRefGoogle Scholar
Alandoli, E. A., Sulaiman, M. and Rashid, M. Z. A., “Robustness and disturbance rejection of PD/H-8 integrated controller for flexible,” J. Eng. Sci. Technol. Rev. 21(1), 27–36 (2019).CrossRefGoogle Scholar
Siradjuddin, I., Behera, L., Mcginnity, T. M. and Coleman, S., “Image-based visual servoing of a 7-DOF robot manipulator using an adaptive distributed fuzzy PD controller,” IEEE/ASME Trans. Mechatron. 19(2), 512–523 (2014).CrossRefGoogle Scholar
Oh, S., Kimura, Y. and Hori, Y., “Reaction Force Control of Robot Manipulator Based on Biarticular Muscle Viscoelasticity Control,” IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Montréal, Canada (2010) pp. 1105–1110.Google Scholar
Kolhe, J. P., Shaheed, M., Chandar, T. S. and Talole, S. E., “Robust control of robot manipulators based on uncertainty and disturbance estimation,” Int. J. Robust. Nonlinear Control 23(1), 104–122 (2011).CrossRefGoogle Scholar
Wilson, J., Charest, M. and Dubay, R., “Non-linear model predictive control schemes with application on a 2 link vertical robot manipulator,” Robot. Comput. Integr. Manuf. 41, 23–30 (2016). doi:10.1016/j.rcim.2016.02.003.CrossRefGoogle Scholar
Xu, J. and Qiao, L., “Robust adaptive PID control of robot manipulator with bounded disturbances,” Math. Probl. Eng. 2013, 1–14 (2013). doi:10.1155/2013/535437.Google Scholar
Guechi, E., Bouzoualegh, S., Zennir, Y. and Blažiè, S., “MPC control and LQ optimal control of a two-link robot arm: A comparative study,” Machines 6(3), 1–14 (2018).CrossRefGoogle Scholar
Rojas, J. H. C., Serrezuela, R. R., López, J. A. Q. and Perdomo, K. L. R., “LQR hybrid approach control of a robotic arm two degrees of freedom,” Int. J. Appl. Eng. Res. 11(17), 9221–9228 (2016).Google Scholar
Al-dabbagh, R. D., Kinsheel, A., Mekhilef, S., Sapiyan, M. and Shamshirband, S., “System identification and control of robot manipulator based on fuzzy adaptive differential evolution algorithm,” Adv. Eng. Softw. 78, 60–66 (2014). doi:10.1016/j.advengsoft.2014.08.009.CrossRefGoogle Scholar
Zhou, Q., Li, H. and Shi, P., “Decentralized adaptive fuzzy tracking control for robot finger dynamics,” IEEE Trans. Fuzzy Syst. 23(3), 501–510 (2015).CrossRefGoogle Scholar
Hasan, A. T., Ismail, N., Hamouda, A. M. S., Aris, I., Marhaban, M. H., and Al-assadi, H. M. A. A., “Artificial neural network-based kinematics Jacobian solution for serial manipulator passing through singular configurations,” Adv. Eng. Softw. 41(2), 359–367 (2010).CrossRefGoogle Scholar
Tang, L., Liu, Y. and Tong, S., “Adaptive neural control using reinforcement learning for a class of robot manipulator,” Neural Comput. Applic 25(1), 135–141 (2014).CrossRefGoogle Scholar
Kumar, N., Panwar, V., Sukavanam, N., Sharma, S. P. and Borm, J. H., “Neural network-based nonlinear tracking control of kinematically redundant robot manipulators,” Math. Comput. Model. 53(9–10), 1889–1901 (2011).CrossRefGoogle Scholar
Yang, C., Wang, X., Cheng, L. and Ma, H., “Neural-learning-based telerobot control with guaranteed performance,” IEEE Trans. Cybern. 47(10), 3148–3159 (2017).CrossRefGoogle ScholarPubMed
Chen, N., Song, F., Li, G., Sun, X. and Ai, C., “An adaptive sliding mode backstepping control for the mobile manipulator with nonholonomic constraints,” Commun. Nonlinear Sci. Numer. Simul. 18(10), 2885–2899 (2013).CrossRefGoogle Scholar
Jalali, A., Piltan, F., Keshtgar, M. and Jalali, M., “Colonial competitive optimization sliding mode controller with application to robot manipulator,” Int. J. Intell. Syst. Appl. 5(7), 50–56 (2013).Google Scholar
Fallaha, C. J., Saad, M., Kanaan, H. Y. and Al-haddad, K., “Sliding-mode robot control with exponential reaching law,” IEEE Trans. Ind. Electron. 58(2), 600–610 (2011).CrossRefGoogle Scholar
Rigatos, G., Siano, P. and Raffo, G., “An H-infinity nonlinear control approach for multi-DOF robotic manipulators,” IFAC-PapersOnLine 49(12), 1406–1411 (2016).CrossRefGoogle Scholar
Rigatos, G. and Siano, P., “A new nonlinear H-infinity feedback control approach to the problem of autonomous robot navigation,” Intell. Ind. Syst. 1(3), 179–186 (2015).CrossRefGoogle Scholar
Chaudhary, H., Panwar, V., Prasad, R. and Sukavanam, N., “Adaptive neuro fuzzy based hybrid force/position control for an industrial robot manipulator,” J. Intell. Manuf. 27(6), 1299–1308 (2016).CrossRefGoogle Scholar
Wai, R. and Muthusamy, R., “Design of fuzzy-neural-network-inherited backstepping control for robot manipulator,” IEEE Trans. Fuzzy Syst. 22(4), 709–722 (2014).CrossRefGoogle Scholar
Wai, R. and Muthusamy, R., “Fuzzy-neural-network inherited sliding-mode control for robot manipulator including actuator dynamics,” IEEE Trans. Neural Networks Learn. Syst. 24(2), 274–287 (2013).Google ScholarPubMed
Wang, Y., Gu, L., Xu, Y. and Cao, X., “Practical tracking control of robot manipulators with continuous fractional-order nonsingular,” IEEE Trans. Ind. Electron. 63(10), 6194–6204 (2016).CrossRefGoogle Scholar
Soltanpour, M. R., Khooban, M. H. and Soltani, M., “Robust fuzzy sliding mode control for tracking the robot manipulator in joint space and in presence of uncertainties,” Robotica 32(3), 433–446 (2014).CrossRefGoogle Scholar
Ahmad, M. A. and Mohamed, Z., “Modelling and simulation of vibration and input tracking control of a single-link flexible manipulator,” Pertanika J. Sci. Technol. 18(1), 61–76 (2010).Google Scholar
Dong, X.-J., Meng, G. and Peng, J.-C., “Vibration control of piezoelectric smart structures based on system identification technique: Numerical simulation and experimental study,” J. Sound Vib. 297(3), 680–693 (2006).CrossRefGoogle Scholar
Araghi, L., Korayem, M. and Nikoobin, A., “Linear-Quadratic-Gaussian (LQG) Controller for Two link-robotic Manipulator Control,” the World Congress on Engineering and Computer Science, San Francisco, USA (2008), pp. 1–6.Google Scholar
Hongyan, L., Yumei, H., Wenhao, S. and Hongwei, X., “Design of adaptive fuzzy controller for flexible link manipulator,” Proceedings of the IEEE International Conference on Industrial Technology (2008) pp. 3–6.Google Scholar