Research On Intelligent Tracking Control For Nonholonomic Mobile Robot

Wheeled mobile robot,as an important member of the robot family,is widely used because of its simple structure and high energy efficiency.Moreover,The wheeled mobile robot is regarded as a typical nonlinear uncertain system with nonholonomic constraints.This paper focuses on the trajectory tracking problem of mobile robot.In chapter 2,the concepts of nonholonomic constraint and nonholonomic system are introduced.Then the kinematical and dynamical models of nonholonomic mobile robot are established and analyzed.In addition,the paper introduces the related mathematical theorems and lemmas which are needed in the research of the theoretical algorithms,and provides the basic knowledge for the following research.Considering the modeling errors and the unknown upper bounds,the chapter 3designs a hybrid robust control method for nonholonomic mobile robot based on neural network.A diagonal recurrent neural network(DRNN)is utilized to approximate the system modeling error,and robust H?control is employed to suppress the influence of the external disturbance and the DRNN approximation error on the system control performance.Based on Lyapunov stability theory,it is proved that the closed-loop system is stable,and the tracking error and the adaptive error of DRNN weights are bounded.Besides,the robust tracking performance of the control system can be guaranteed.The simulation results show that the proposed intelligent hybrid control method has better tracking performance than the computed torque method.In general,the tracking error can converge to the equilibrium point in finite time by using the terminal sliding mode control method.However,the chattering phenomenon of the control torque still exists,which limits its application in the tracking control of mobile robot.Therefore,to reduce the chattering and achieve the finite time convergence,the chapter 4 puts forward the method which combines emotional learning algorithm with terminal sliding mode control method for tracking control of nonhonlomic mobile robot.In this paper,the emtional learning algorithm isused to approximate the nonlinear model of the mobile robot,and terminal sliding mode control method is used to achieve the finite-time control.Based on the Lyapunov theory,the closed-loop control system is proved to be stable.Compared with the conventional sliding mode control method and terminal sliding mode method,the simulation results show that the proposed terminal sliding mode control method which is based on emotional learning algorithm can suppress the chattering phenomenon better.Moreover,the tracking error of the system can converge to the equilibrium point in finite time.Considering that the velocity information of the mobile robot is unknown.In the chapter 5,the velocities of the robot are reconstructed by using the fuzzy state observer.Fuzzy logic is used to deal with the modeling uncertainties of nonholonomic mobile robot,and the robust term is introduced to suppress the influence that attributes to external disturbance and fuzzy logic approximation error on the performance of the system.Based on the strict positive real Lyapunov design method,the error between the reconstructed velocities and the real velocities are bounded.Then,based on the reconstructed velocities of the observer and the known positions,a fuzzy adaptive output feedback controller for nonholonomic mobile robot is proposed.The adaptive laws of the fuzzy parameters are designed based on Lyapunov stability,and all state variables and tracking errors of the closed-loop system are bounded.Finally,the simulation results show the effectiveness of the proposed method.