A robust intelligent controller-based motion control of a wheeled mobile robot

Ardeshiri, Reza Rouhi; Gheisarnejad, Meysam; Tavan, Mohammad Reza; Vafamand, Navid; Khooban, Mohammad‐Hassan

doi:10.1177/01423312221088389

Cited by 3 publications

(1 citation statement)

References 43 publications

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“…There are mainly two research interests in the uncertainties issue, that is, control design and uncertainties description. To achieve the control objective for WMR, scholars have tried to propose many efficient control strategies based on the classic control method, such as Lyapunov-based control, 9 sliding mode control, 10 H ∞ control, 11 adaptive control, 12 fuzzy control, 13 neural network control. 14 Although these control methods achieve some outstanding performance for WMR, for instance, fast convergence rate, high accuracy, and robustness against uncertainties, they also have some drawbacks.…”

Section: Introductionmentioning

confidence: 99%

Cooperative game-oriented optimal robust control for an uncertain wheeled mobile robot with position constraints

Zheng,

Zhao,

Zheng

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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The trajectory tracking control performance of the wheeled mobile robot (WMR) is subject to position constraints, system uncertainties, and external disturbances. This paper explores the mechanism of the position constraints (equality and inequality) and considers the system uncertainties to be time-varying but bounded with fuzzy prescribed bounds. To solve the position constraints and uncertainties problems, a cooperative game-oriented optimal robust control method is proposed to provide high-precision, fast-response performance and robustness for WMR. First, a creative diffeomorphism transformation is proposed to convert the bounded state variables (subject to inequality constraints) into unbounded state variables. Accordingly, a restructured WMR system with the new state variables is established, which is free from inequality constraints. The uncertainties’ bound is described as a fuzzy number by employing fuzzy set theory, which builds the fuzzy dynamic system of the WMR. Second, the control goal for this study is to drive the WMR to follow the position constraints despite uncertainties. An optimal robust control is developed to guarantee that the tracking errors of the WMR converge to a predefined neighborhood of origin. Using Lyapunov stability analysis, a fuzzy performance index is constructed, including steady-state performance, time performance, and control effort. The fuzzy performance index is employed as the cost function based on the cooperative game theory. The optimal control design is formulated to seek the Pareto-optimal solution of control parameters. Finally, the stability analysis and comparative experiments demonstrate that the proposed control algorithm can ensure the WMR’s superior trajectory tracking convergence performance and strong robustness against uncertainties/disturbances.

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Section: Introductionmentioning

confidence: 99%

Cooperative game-oriented optimal robust control for an uncertain wheeled mobile robot with position constraints

Zheng,

Zhao,

Zheng

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

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An Adaptive Control Based on Improved Gray Wolf Algorithm for Mobile Robots

Xue,

Lu,

Zhang

2024

Applied Sciences

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In this paper, a novel intelligent controller for the trajectory tracking control of a nonholonomic mobile robot with time-varying parameter uncertainty and external disturbances in the case of tire hysteresis loss is proposed. Based on tire dynamics principles, a dynamic and kinematic model of a nonholonomic mobile robot is established, and the neural network approximation model of the system’s nonlinear term caused by many coupling factors when the robot enters a roll is given. Then, in order to adaptively estimate the unknown upper bounds on the uncertainties and perturbations for each subsystem in real time, a novel adaptive law employed online as a gain parameter is designed to solve the problem of inter-system coupling and reduce the transient response time of the system with lower uncertainties. Additionally, based on improved gray wolf optimizer and fuzzy system techniques, an adaptive algorithm using the gray wolf optimizer study space as the output variable of the fuzzy system to expand the search area of the gray wolves is developed to optimize the controller parameters online. Finally, the efficacy of the proposed intelligent control scheme and the feasibility of the proposed algorithm are verified by the 2023a version of MATLAB/Simulink platform.

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Application of Compensation Algorithms to Control the Speed and Course of a Four-Wheeled Mobile Robot

Shadrin,

Krasavin,

Nazenova

et al. 2024

Sensors

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This article presents a tuned control algorithm for the speed and course of a four-wheeled automobile-type robot as a single nonlinear object, developed by the analytical approach of compensation for the object’s dynamics and additive effects. The method is based on assessment of external effects and as a result new, advanced feedback features may appear in the control system. This approach ensures automatic movement of the object with accuracy up to a given reference filter, which is important for stable and accurate control under various conditions. In the process of the synthesis control algorithm, an inverse mathematical model of the robot was built, and reference filters were developed for a closed-loop control system through external effect channels, providing the possibility of physical implementation of the control algorithm and compensation of external effects through feedback. This combined approach allows us to take into account various effects on the robot and ensure its stable control. The developed algorithm provides control of the robot both when moving forward and backward, which expands the capabilities of maneuvering and planning motion trajectories and is especially important for robots working in confined spaces or requiring precise movement into various directions. The efficiency of the algorithm is demonstrated using a computer simulation of a closed-loop control system under various external effects. It is planned to further develop a digital algorithm for implementation on an onboard microcontroller, in order to use the new algorithm in the overall motion control system of a four-wheeled mobile robot.

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A robust intelligent controller-based motion control of a wheeled mobile robot

Cited by 3 publications

References 43 publications

Cooperative game-oriented optimal robust control for an uncertain wheeled mobile robot with position constraints

Cooperative game-oriented optimal robust control for an uncertain wheeled mobile robot with position constraints

An Adaptive Control Based on Improved Gray Wolf Algorithm for Mobile Robots

Application of Compensation Algorithms to Control the Speed and Course of a Four-Wheeled Mobile Robot

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