Tracking control of mobile robots: a case study in backstepping
Automatica (Journal of IFAC)
Nonlinear and Adaptive Control Design
Nonlinear and Adaptive Control Design
Information Sciences: an International Journal
International Journal of Robotics Research
Development of membrane controllers for mobile robots
Information Sciences: an International Journal
Information Sciences: an International Journal
Robust adaptive control of nonholonomic mobile robot with parameter and nonparameter uncertainties
IEEE Transactions on Robotics
Modeling and Analysis of Skidding and Slipping in Wheeled Mobile Robots: Control Design Perspective
IEEE Transactions on Robotics
A Sliding-Mode-Control Law for Mobile Robots Based on Epipolar Visual Servoing From Three Views
IEEE Transactions on Robotics
Adaptive control for mobile robot using wavelet networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Control of a nonholonomic mobile robot using neural networks
IEEE Transactions on Neural Networks
Neural network control of a class of nonlinear systems with actuator saturation
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Information Sciences: an International Journal
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This paper presents a neural-network-based adaptive control approach for path tracking and obstacle avoidance of a class of mobile robots in the presence of unknown skidding, slipping, and torque saturation. The model of mobile robots consists of kinematics and dynamics considering skidding and slipping where all robot parameters as well as skidding and slipping effects are unknown. The proposed adaptive controller is designed using systematic and recursive design methodologies, without the assumption of perfect velocity tracking, where the function approximation technique using neural networks is employed to compensate unknown nonlinear functions including the model uncertainties and bounds of the skidding and slipping. From Lyapunov-stability analysis, it is shown that all signals of the controlled closed-loop system are semiglobally uniformly ultimately bounded, point tracking errors converge to an adjustable neighborhood of the origin outside the obstacle detection region, and the obstacle avoidance is guaranteed inside the region. The effectiveness of the proposed control system is demonstrated by simulation results.