This article proposes a robust and adaptive controller for industrial robot arms with multiple degrees of freedom without the need for velocity measurement. Many of the controllers designed for manipulators are model-based and require detailed knowledge of the system model. In contrast to these methods, this paper proposes a model-free controller using the Philips q-Bernstein operator as universal approximator. The designed controller can approximate uncertainties including external disturbances and unmodeled dynamics based on its universal approximation capability. Besides, most of the controllers revealed for robot arms are torque-based, which is not a realistic presumption from a practical point of view. In the proposed control method, the voltage applied to the actuator is considered as the control signal. However, unlike many voltage-based methods, the need to know the exact models of the system and the actuator has been eliminated in the presented method. Also, adaptive rules are extracted during the Lyapunov analysis to ensure system stability. Finally, to analyze the performance of the presented controller, this method is simulated for an industrial robot arm, and the results are analyzed. The proposed methodology is also compared to those of a strong state-of-the-art approximator, the Chebyshev neural network.

This article addresses the problem of pose and force control in a cooperative system comprised of multiple n-degree-of-freedom (n-DOF) electrically driven robotic arms that move a payload. The proposed controller should be capable of maintaining the position and orientation of the payload in the desired path. In addition, the force exerted by robot end effectors on the object must remain limited. The system has unmodeled dynamics, and measuring the robot joint velocities is impossible. Therefore, a FAT-based observer–controller is designed to estimate the uncertainty and velocities based on universal approximation property of Fourier series expansion. The stability of the system is confirmed based on Lyapunov’s stability theorem. Finally, the proposed adaptive controller–observer is applied on two 3-DOF cooperative robotic arms carrying a payload, and the results are precisely analyzed. The results of the proposed approach are also compared with two state-of-art powerful approximation method.

This paper aims at developing a novel method to assess the kinematic reliability of robotic manipulators based on the fuzzy theory. The kinematic reliability quantifies the probability of obtaining positioning errors within acceptable limits. For this purpose, the fuzzy reliability evaluates the effect of the joint clearances on the end-effector position to compute a failure possibility index. As an alternative to the conventional methods reported in the literature, this failure possibility index conveys a novel assessment of the kinematic performance. The numerical results are compared with the well-known probabilistic approach based on the Monte Carlo simulation.

This paper proposes a robust controller for the generation of stable limit cycles in multi-input mechanical systems subjected to model uncertainties. The proposed idea is based on Port-Controlled Hamiltonian (PCH) model and energy-based control by considering the Hamiltonian function as the Lyapunov function. For this purpose, first, a nominal controller is designed by shaping the energy function of the system according to the structure of the desired limit cycle. Then, an additional robustifying control term is designed based on the integral sliding mode method with the selection of an appropriate sliding surface. Finally, computer simulations for two practical case studies are provided to confirm the effectiveness of the proposed controller in the generation of stable limit cycles in the presence of uncertainties.

In this paper, a multi-objective design optimization of the 3-UPU translational parallel manipulator is presented. Based on a new algorithm, which combines the genetic algorithms and the Krawczyk operator, the robot position error is minimized and the robot design parameters tolerances are maximized, simultaneously. The results show that the designer can maintain the manipulator accuracy by using a specific size of the base, and can restrict its tolerance even by enlarging the actuators’ tolerance intervals. This algorithm is also used to determine the maximum design parameters tolerances for an allowable robot position error. The proposed algorithm can be extended to optimize other types of robots.

A robust adaptive nonlinear asymptotic regulating control law is designed for dynamically positioned vessels exposed to unknown time-varying external disturbances incorporating Fuzzy Logic Systems (FLSs), projection operators, and the “robustifying” term into the vectorial backstepping technique. The FLSs approximate the vessel unknown dynamics and the update laws based on the online projection operators update the fuzzy weight vectors. The robustifying term handles the external disturbances and the fuzzy approximation errors. The designed Dynamic Positioning (DP) control law achieves asymptotic regulation of the vessel's position and heading and makes the other signals in the DP closed-loop control system of vessels be uniformly ultimately bounded. Simulations based on the Marine System Simulator toolbox validate the designed DP control law.

Seismic hazard in low seismicity areas of Europe has traditionally been considered insignificant. However, in the light of the recently conducted paleoseismic studies along the Rhine Graben, a revision is required. Previously applied standard probabilistic seismic hazard assessment (PSHA) methods, using Poissonian approach for the earthquake occurrence, can now be substituted by renewal models where fault parameters such as the maximum magnitude, recurrence interval and the elapsed time since the last occurrence of a large earthquake, can be utilized. In this study, the application and the influence of the available paleoseismic data in the Lower Rhine Graben to seismic hazard analysis is demonstrated. The resulting hazard maps, when compared to the standard PSHA using Poissonian approach, indicate a more precise geographical distribution of the estimated seismic hazard levels. The influence of the paleoseismic data seem to be less important for return periods less than a 1000 years. Among the different input models, the highest values reach to 170 cm/sec2 for a 1000 year return period using a combination of Poissonian and renewal models.

This paper addresses the problem of trajectory tracking control in mobile robots under velocity limitations. Following the results reported in ref. [1], the problem of trajectory tracking considering control actions constraint is focused and the zero convergence of the tracking errors is demonstrated. In this work, the original methodology is expanded considering a controller that depends not only on the position but also on the velocity. A simple scheme is obtained, which can be easily implemented in others controllers of the literature. Experimental results are presented and discussed, demonstrating the good performance of the controller.

Airborne electromagnetics (AEM) is an effective technique for geophysical investigations of the shallow subsurface and has successfully been applied in various geological settings to analyse the depositional architecture of sedimentary systems for groundwater and environmental purposes. However, interpretation of AEM data is often restricted to 1D inversion results imaged on resistivity maps and vertical resistivity sections. The integration of geophysical data based on AEM surveys with geological data is often missing and this deficiency can lead to uncertainties in the interpretation process. The aim of this study is to provide an improved methodology for the interpretation of AEM data and the construction of more realistic 3D geological subsurface models. This is achieved by the development of an integrated workflow and 3D modelling approaches based on combining different geophysical and geological data sets (frequency-domain helicopter-borne electromagnetic data (HFEM), time-domain helicopter-borne electromagnetic data (HTEM), three 2D reflection seismic sections and 488 borehole logs). We used 1D inversion results gained from both HFEM and HTEM surveys and applied a 3D resistivity gridding procedure based on geostatistical analyses and interpolation techniques to create continuous 3D resistivity grids. Subsequently, geological interpretations have been performed by combining with, and validation against, borehole and reflection seismic data. To verify the modelling results and to identify uncertainties of AEM inversions and interpretation, we compared the apparent resistivity values of the constructed 3D geological subsurface models with those of AEM field measurements. Our methodology is applied to a test site near Cuxhaven, northwest Germany, where Neogene sediments are incised by a Pleistocene tunnel valley. The Neogene succession is subdivided by four unconformities and consists of fine-grained shelf to marginal marine deposits. At the end of the Miocene an incised valley was formed and filled with Pliocene delta deposits, probably indicating a palaeo-course of the River Weser or Elbe. The Middle Pleistocene (Elsterian) tunnel valley is up to 350 m deep, 0.8–2 km wide, and incised into the Neogene succession. The unconsolidated fill of the Late Miocene to Pliocene incised valley probably formed a preferred pathway for the Pleistocene meltwater flows, favouring the incision. Based on the 3D AEM resistivity model the tunnel-valley fills could be imaged in high detail. They consist of a complex sedimentary succession with alternating fine- and coarse-grained Elsterian meltwater deposits, overlain by glaciolacustrine (Lauenburg Clay Complex) and marine Holsteinian interglacial deposits. The applied approaches and results show a reliable methodology, especially for future investigations of similar geological settings. The 3D resistivity models clearly allow a distinction to be made between different lithologies and enables the detection of major bounding surfaces and architectural elements.

This paper investigates the trajectory tracking of a Stewart platform, which is a typical multi-input multi-output nonlinear system, with unmodeled dynamics, parameter uncertainties, friction, and unpredictable actuator faults. An adaptive vector sliding mode fault-tolerant control law is derived to ensure the system is insensitive to uncertainties and drive the state variable errors of the closed-loop system to converge to the origin. Moreover, novel adaptive laws are proposed to update the upper boundary of uncertainty according to the actual system state, which greatly reduces the chattering of sliding mode control. Furthermore, velocity signals are estimated by introducing a simple nonlinear observer, resulting in the proposed controller requiring position measurements only. Finally, numerical simulations illustrate the effectiveness of the proposed control scheme.

In this short note, we investigate the framework where agents or players have some uncertainties upon their payoffs or losses, the behavior (or the type, number or any other characteristics) of other players. More specifically, we introduce an extension of the concept of Nash equilibria that generalize different solution concepts called by their authors, and depending on the context, either as robust, ambiguous, partially specified or with uncertainty aversion. We provide a simple necessary and sufficient condition that guarantees its existence and we show that it is actually a selection of conjectural (or self-confirming) equilibria. We finally conclude by how this concept can and should be defined in games with partial monitoring in order to preserve existence properties.

A five years geological mapping project, in which the Netherlands Continental Shelf has been re-examined using all publicly available data, resulted in an important update of the existing dataset. The stratigraphy of over 400 wells has been re-interpreted. New depth and thickness grids, based mainly on the interpretation of 3D seismic data have been produced for the most important stratigraphic intervals from Permian Upper Rotliegend to Neogene. New reservoir grids describe the top, base and thickness of 30 (potential) reservoir units in the area. In addition, the uncertainty related to interpretation and further processing of the data has been assessed. This resulted in maps displaying the standard deviation for the depth of the main stratigraphic intervals. Based on these results and the data already available for the onshore area, an updated structural element map was made for the Netherlands.

This article proposes a combined theoretical and experimental approach to assess andquantify the global uncertainty of a high-speed camera velocity measurement. The study isdivided in five sections: firstly, different sources of measurement uncertaintiesperformed by a high-speed camera are identified and quantified. They consist ofgeometrical uncertainties, pixel discretisation uncertainties or optical uncertainties.Secondly, a global uncertainty factor, taking into account the previously identifiedsources of uncertainties, is computed. Thirdly, a sensibility study of the camera set-upparameters is performed, allowing the experimenter to optimize these parameters in orderto minimize the final uncertainties. Fourthly, the theoretical computed uncertainty iscompared with experimental measurements. Good concordance has been found. Finally, thevelocity measurement uncertainty study is extended to continuous displacement measurementsas a function of time. The purpose of this article is to propose all the mathematicaltools necessary to quantify the individual and global uncertainties, to highlight theimportant aspects of the experimental set-up, and to give recommendations on how toimprove a specific set-up in order to minimize the global uncertainty. Taking all theseinto account, it has been shown that highly dynamic phenomena such as a ballisticphenomenon can be measured using a high-speed camera with a global uncertainty of lessthan 2%.

This paper proposes a simple fuzzy sliding mode control to achieve the best trajectory tracking for the robot manipulator. In the core of the proposed method, by applying the feedback linearization technique, the known dynamics of the robot's manipulator is removed; then, in order to overcome the remaining uncertainties, a classic sliding mode control is designed. Afterward, by applying the TS fuzzy model, the classic sliding mode controller is converted to fuzzy sliding mode controller with very simple rule base. The mathematical analysis shows that the robot manipulator with the new proposed control in tracking the robot manipulator in presence of uncertainties has the globally asymptotic stability. Finally, to show the performance of the proposed method, the controller is simulated on a robot manipulator with two degrees of freedom as case study of the research. Simulation results demonstrate the superiority of the proposed control scheme in presence of the structured and unstructured uncertainties.