Robust adaptive control for a nonholonomic mobile robot with unknown parameters  

作　　者：Jinbo WU Guohua XU Zhouping YIN 

机构地区：[1]School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan Hubei 430074, China [2]State Key Lab of Digital Manufacturing and Technology, Huazhong University of Science and Technology, Wuhan Hubei 430074, China

出　　处：《控制理论与应用（英文版）》2009年第2期212-218,共7页

基　　金：partly supported by the National Natural Science Foundation of China (No.50625516);the 863 program of China(No.2006AA09Z203,2006AA04A110)

摘　　要：A robust adaptive controller for a nonholonomic mobile robot with unknown kinematic and dynamic parameters is proposed. A kinematic controller whose output is the input of the relevant dynamic controller is provided by using the concept of backstepping. An adaptive algorithm is developed in the kinematic controller to approximate the unknown kinematic parameters, and a simple single-layer neural network is used to express the highly nonlinear robot dynamics in terms of the known and unknown parameters. In order to attenuate the effects of the uncertainties and disturbances on tracking performance, a sliding mode control term is added to the dynamic controller. In the deterministic design of feedback controllers for the uncertain dynamic systems, upper bounds on the norm of the uncertainties are an important clue to guarantee the stability of the closed-loop system. However, sometimes these upper bounds may not be easily obtained because of the complexity of the structure of the uncertainties. Thereby, simple adaptation laws are proposed to approximate upper bounds on the norm of the uncertainties to address this problem. The stability of the proposed control system is shown through the Lyapunov method. Lastly, a design example for a mobile robot with two actuated wheels is provided and the feasibility of the controller is demonstrated by numerical simulations.A robust adaptive controller for a nonholonomic mobile robot with unknown kinematic and dynamic parameters is proposed. A kinematic controller whose output is the input of the relevant dynamic controller is provided by using the concept of backstepping. An adaptive algorithm is developed in the kinematic controller to approximate the unknown kinematic parameters, and a simple single-layer neural network is used to express the highly nonlinear robot dynamics in terms of the known and unknown parameters. In order to attenuate the effects of the uncertainties and disturbances on tracking performance, a sliding mode control term is added to the dynamic controller. In the deterministic design of feedback controllers for the uncertain dynamic systems, upper bounds on the norm of the uncertainties are an important clue to guarantee the stability of the closed-loop system. However, sometimes these upper bounds may not be easily obtained because of the complexity of the structure of the uncertainties. Thereby, simple adaptation laws are proposed to approximate upper bounds on the norm of the uncertainties to address this problem. The stability of the proposed control system is shown through the Lyapunov method. Lastly, a design example for a mobile robot with two actuated wheels is provided and the feasibility of the controller is demonstrated by numerical simulations.

关 键 词：Nonholonomic constraints Mobile robot Sliding mode control Adaptive control ROBUSTNESS Neural network 

分 类 号：TP273.2[自动化与计算机技术—检测技术与自动化装置] TP242[自动化与计算机技术—控制科学与工程]