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Summary: This paper presents an Adaptive Terminal Integral Sliding Mode Control (ATISMC) scheme for trajectory tracking problems applied to a differential Wheeled Mobile Robot (WMR). First, a terminal integral sliding variable is designed. Based on the finite‐time concept, an adaptive control law has been developed in which a switching gain is adjusted adaptively by using a novel strategy. This control method aims to deal with unknown bounded disturbances and uncertainties. Moreover, it allows fast convergence of the system states to an equilibrium point. The main features of the proposed ATISMC are its robustness, fast convergence rate, and chattering avoidance. To realize trajectory tracking for WMR, the ATISMC is incorporated into a double closed loop scheme. Stability analysis is performed using the Lyapunov stability theory. Numerical simulations and real‐time experiments demonstrate the feasibility of the proposed controller scheme. A comparison study with the classical ISMC was performed to show the superiority of the developed method. [ABSTRACT FROM AUTHOR]

In this paper, an Improved Extended State Observer-based Finite-Time adaptive sliding mode control, is investigated for trajectory tracking control of a wheeled mobile robot. First, a novel finite-time adaptive sliding mode control, based on the fractional power of the sliding surface, is developed to deal with the chattering problem. Moreover, this strategy improves the convergence rate by adjusting online the switching part in sliding mode control. Second, an improved Non-linear ESO is employed to reconstruct and compensate for the unknown disturbances. To complete the trajectory tracking control, the kinematic algorithm is introduced. Theoretically, the proposed control scheme converges within finite-time thanks to the Lyapunov method. Finally, numerical simulations show the efficiency of the designed controller. [ABSTRACT FROM AUTHOR]

This paper presents a fuzzy adaptive sliding mode controller (FASMC) for electrically driven wheeled mobile robot for trajectory tracking task in the presence of uncertainties and disturbances. First, a finite-time kinematic controller is developed to compute the auxiliary velocity vector. Second, the FASMC, based on the nonlinear dynamic model of the robot and its actuators, is used to guarantee the stability and the convergence of the closed-loop system. Moreover, by employing the advantages of the fuzzy logic systems, the developed controller ensures the robustness of the system against dynamic disturbances and uncertainties, the smoothness of the computing voltage against the chattering phenomenon, and the optimal convergence of the velocity and posture errors. The Lyapunov theory is used to analyse the stability of this algorithm. In order to evaluate the effectiveness of the developed method, numerical simulations are done in the Mahlab/Simulink environment. [ABSTRACT FROM AUTHOR]