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Nonlinear DOB-based explicit NMPC for station-keeping of a multi-vectored propeller airship with thrust saturation

Published online by Cambridge University Press:  15 November 2018

Y. Wen ,
L. Chen ,
Y. Wang ,
D. Sun ,
D. Duan  and
J. Liu
Y. Wen
Affiliation:
School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai China
L. Chen*
Affiliation:
School of Air Transportation Shanghai University of Engineering Science Shanghai China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China
Y. Wang
Affiliation:
School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai China
D. Sun
Affiliation:
School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai China
D. Duan
Affiliation:
School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai China
J. Liu
Affiliation:
State Key Laboratory of Robotics Shenyang Institute of Automation (SIA) Chinese Academy of Sciences (CAS) Shenyang, PR China
*
chen2006@sjtu.edu.cn
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Abstract

A nonlinear station-keeping control method for a multi-vectored propeller airship under unknown wind field with thrust saturation is developed, which is composed of three modules: nonlinear model predictive controller (NMPC), disturbance observer (DOB) and tracking differentiator (TD). The nonlinear kinematics and dynamics models are introduced, and the wind effect is considered by the wind-induced aerodynamic force. Based on both models, an explicit NMPC is designed. Then a nonlinear DOB is introduced to estimate the wind disturbance. A TD, showing the relationship between the maximum propulsion force and the maximum flight acceleration, is proposed to handle the thrusts’ amplitude saturation. Stability analysis shows that the closed-loop system is globally asymptotically stable. Simulations for a multi-vectored propeller airship are conducted to demonstrate the robustness and effectiveness of the proposed method.

Keywords

Model predictive controldisturbance observertracking differentiatorstation-keepingsaturation
Type
Research Article
Information
The Aeronautical Journal , Volume 122 , Issue 1257 , November 2018 , pp. 1753 - 1774
Copyright
© Royal Aeronautical Society 2018 

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References

1. Yang, X.X. and Liu, D.N. Conceptual design of stratospheric airships focusing on energy balance, Journal of Aerospace Engineering, March 2018, 31, (2), pp 04017094.Google Scholar
2. Li, Y.W., Nahon, M. and Sharf, I. Airship dynamics modeling: A literature review, Progress in Aerospace Sciences, April 2011, 47, (3), pp 217–239.Google Scholar
3. Yang, X.X. Prediction of thermal behavior and trajectory of stratospheric airships during ascent based on simulation, Advances in Space Research, June 2016, 57, (11), pp 2326–2336.Google Scholar
4. Schmidt, D.K. Modeling and near-space stationkeeping control of a large high-altitude airship, Journal of Guidance, Control, and Dynamics, March 2007, 30, (2), pp 540–547.Google Scholar
5. Azinheira, J.R., Moutinho, A. and De Paiva, E.C. Airship hover stabilization using a backstepping control approach, Journal of Guidance, Control, and Dynamics, July 2006, 29, (4), pp 903–914.Google Scholar
6. Acosta, D.M. and Joshi, S.S. Adaptive nonlinear dynamic inversion control of an autonomous airship for the exploration of Titan, AIAA Guidance, Navigation and Control Conference and Exhibit, 20–23 Augst 2007, Hilton Head, SC, AIAA 2007-6502.Google Scholar
7. Saiki, H., Fukao, T., Urakubo, T. and Kohno, T. Hovering control of outdoor blimp robots based on path following, Control Applications (CCA), 2010 IEEE International Conference on Systems and Control, 8–10 September 2010, Yokohama, Japan, pp 2124–2129.Google Scholar
8. Zheng, Z.W., Huo, W. and Wu, Z. Hovering control for an underactuated stratospheric airship, Proceedings of the 32nd Chinese Control Conference, 26–28 July 2013, Xi’an, China, pp 4238–4243.Google Scholar
9. Hong, L.H., Lin, X.W. and Lan, W.Y. One dimensional trajectory optimization for horizontal position correction of spot hovering stratosphere airship, 25th Chinese Control and Decision Conference (CCDC), 25–27 May 2013, Guiyang, China, pp 643–648.Google Scholar
10. Dorrington, G.E. Development of an airship for tropical rain forest canopy exploration, The Aeronautical Journal, August 2005, 109, (1098), pp 361–372.Google Scholar
11. Zheng, Z.W., Zhu, M., Shi, D.L. and Wu, Z. Hovering control for a stratospheric airship in unknown wind, AIAA Guidance, Navigation, and Control Conference, 13–17 January 2014, National Harbor, Maryland, pp. 4238–4243.Google Scholar
12. Chen, W.H., Ballance, D.J., Gawthrop, P.J. and O’Reilly, J. A nonlinear disturbance observer for robotic manipulators, IEEE Transactions on Industrial Electronics, August 2000, 47, (4), pp 932–938.Google Scholar
13. Liu, C.J., Chen, W.H. and Andrews, J. Trajectory tracking of small helicopters using explicit nonlinear MPC and DOBC, IFAC Proceedings Volumes, January 2011, 44, (1), pp 1498–1503.Google Scholar
14. Wang, Y.Y., Gao, Y.B., Karimi, H.R., Shen, H. and Fang, Z.J. Sliding mode control of fuzzy singularly perturbed systems with application to electric circuit, IEEE Transactions on Systems, Man, and Cybernetics: Systems, August 2017, https://doi.org/10.1109/TSMC.2017.2720968.Google Scholar
15. Chen, W.H., Yang, J., Guo, L. and Li, S.H. Disturbance observer based control and related methods: an overview, IEEE Transactions on Industrial Electronics, February 2016, 63, (2), pp 1083–1095.Google Scholar
16. Camacho, E.F. and Bordons, C. Model Predictive Control. Spring Press, London, UK, 1999.Google Scholar
17. Wang, Y., Xia, Y., Shen, H. and Zhou, P. SMC design for robust stabilization of nonlinear Markovian jump singular systems, IEEE Transactions on Automatic Control, January 2018, 63, (1), pp 219–224.Google Scholar
18. Grancharova, A. and Johansen, T.A. Explicit Nonlinear Model Predictive Control: Theory and Applications, 2012, Springer, Berlin, Heidelberg.Google Scholar
19. Han, J.Q. Active disturbance rejection control technique, 2007, National Defense Industry Press, Beijing, China.Google Scholar
20. Han, J.Q. From PID to active disturbance rejection control, IEEE Transactions on Industrial Electronics, March 2009, 56, (3), pp 900–906; (2009).Google Scholar
21. Chen, L. and Duan, D.P. Statics and Dynamics Flight Mechanics in Atmosphere, 2015, Shanghai Jiao Tong University Press, Shanghai, China.Google Scholar
22. Azinheira, J.R., De Paiva, E.C. and Bueno, S.S. Influence of wind speed on airship dynamics, Journal of Guidance Control & Dynamics , November 2002, 25, (6), pp 1116–1124.Google Scholar
23. Wang, X.L. Study on nonlinear aerodynamic forces and motion of stratospheric airship, PhD thesis, Shanghai Jiao Tong University, Shanghai, China, 2006.Google Scholar
24. Liu, F. Anti-windup controller design for a multi-propeller aerostat, Master’s thesis, Shanghai Jiao Tong University, Shanghai, China, 2016.Google Scholar
25. Chen, L., Zhang, H. and Duan, D.P. Control system design of a multi-vectored thrust stratospheric airship, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, September 2014, 228, (11), pp 2045–2054.Google Scholar
26. Li, S.H., Yang, J., Chen, W.H. and Chen, X.S. Disturbance Observer Based Control: Method and Application. Taylor & Francis Group, CRC Press, New York, USA.Google Scholar
27. Slegers, N. and Costello, M. Nonlinear model predictive control of a 6 dof air vehicle, AIAA Atmospheric Flight Mechanics Conference and Exhibit, 15–18 August 2005, San Francisco, CA, AIAA 2005-6025.Google Scholar
28. Han, J.Q. and Wang, W. Nonlinear tracking-differentiator, Journal of Systems Science & Mathematical Sciences, 1994, 14, (2), pp 177–183.Google Scholar
29. Han, J.Q. and Yuan, L.L. The discrete form of tracking differentiator, Journal of Systems Science and Mathematical Sciences, July 1997, 19, (3), pp 268–273.Google Scholar
30. Wang, Y.Y., Shen, H., Karimi, H.R. and Duan, D.P. Dissipativity-based fuzzy integral sliding mode control of continuous-time ts fuzzy systems, IEEE Transactions on Fuzzy Systems, June 2018, 26, (3), pp 1164–1176.Google Scholar