Trajectory tracking of a nonholonomic mobile robot with parametric and nonparametric uncertainties: A proposed neural control (original) (raw)
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In this paper, a Qzzy neuml dynamics based tracking controller for nonholonomic wheeled mobile robots is proposed. The nonholonomic kinematic constraints are considered in the development of the controller. The proposed model is suitable for both continuous and discrete paths. Fuzzy d e s are fomulated to deal with the discontinuity in path directions. This model is capable of generating smooth velocity commands to drive the robot to track the desired paths. In the situation with large initial errors, the proposed model can automatically generate a smooth curue to reach the desired robot path from an arbitrary initial configuration without any explicit algorithms for the connection curue. At sharp turns, this model can automatically round off the sharp t u n s with a smooth curue. The effectiveness of the proposed tracking controEler is demonstrated by simulation studies. 'This work was supported by Natural Sciences and Engineering tcorresponding author. Email: syang@;uoguelph.ea.
Journal of Intelligent & Fuzzy Systems, 2018
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This article propounds addressing the design of a sliding mode controller with adaptive gains for trajectory tracking of unicycle mobile robots. The dynamics of this class of robots are strong, nonlinear, and subject to external disturbance. To compensate the effect of the unknown upper bounded external disturbances, a robust sliding mode controller based on an integral adaptive law is proposed. The salient feature of the developed controller resides in taking into account that the system is MIMO and the upper bound of disturbances is not priori known. Therefore, we relied on an estimation of each perturbation separately for each subsystem. Hence, the proposed controller provides a minimum acceptable errors and bounded adaptive laws with minimum of chattering problem. To complete the goal of the trajectory tracking, we apply a kinematic controller that takes into account the nonholonomic constraint of the robot. The stability and convergence properties of the proposed tracking dynam...
Neurocomputing, 2017
This paper addresses the trajectory-tracking control problem of mobile robot systems with nonholonomic constraints, in the presence of time-varying parametric uncertainties and external disturbances. This necessitates an accurate controller to meet as much control objectives, as possible. Therefore, this paper deals with an artificial intelligence control technique to design a robust controller to meet the control objectives. The design of the intelligent controller is based on the optimal control theory, the adaptive neural network system, and the robust control technique. The trajectory-tracking problem is solved using the optimal control methodology. Since the nonholonomic wheeled mobile robot is strongly nonlinear, the neural network system is applied to approximate the nonlinear function in the optimal control law. The robust controller, for his part, is then applied to adaptively estimate an unknown upper bound of the time-varying parametric uncertainties, external disturbances and approximation error of the neural network system. The stability of the closed-loop robot system is proven using the optimal control theory and Lyapunov stability analysis. The results of the simulation studies on three typical nonholonomic mobile robots are provided to demonstrate the effectiveness of the proposed controller. In addition, a comparative study with a recent robust adaptive controller shows that our proposed intelligent controller gives better results, in the sense that the output trajectory converges to the steady state faster with smaller tracking error.