| With the rapid development of modern science and technology,mobile robots are widely used in industry and agriculture,military industry,people’s livelihood services and other fields.Trajectory tracking control is one of the basic control problems of mobile robot,and the realization of trajectory tracking control is the basic guarantee for it to complete various complex tasks.Because mobile robots often have nonholonomic characteristics and input coupling constraints,and robots usually work in complex environments,the system is vulnerable to external interference,resulting in the instability of the control system.To solve the above problems,the design and optimization method of tracking controller for mobile robot under coupling constraints,parameter uncertainty and external interference is considered.The research contents can be summarized as follows:(1)Aiming at the problems of external disturbance and parameter uncertainty in the trajectory tracking control system of mobile robot,a double closed-loop structure control method based on extended Kalman disturbance observer is proposed.Firstly,the error equation is established for the kinematic model of the outer loop,and an adaptive control method based on backstepping is designed;Secondly,a disturbance observer based on extended Kalman filter is designed for the inner loop dynamic model to estimate and compensate the state of the dynamic model and the external non-random disturbance;Then,the stability of the double closed-loop system is proved by Lyapunov’s second method;Finally,the effectiveness of this method is verified by simulation tracking circular and linear trajectories.(2)With the different working environment of mobile robot,the weighted matrix parameters of MPC controller need to be adjusted to achieve better trajectory tracking effect.In order to save the cumbersome steps of manually adjusting the controller parameters,a parameter setting method of MPC controller for trajectory tracking of mobile robot is proposed.Through the improved meta heuristic multi-objective optimization method,the objective function of control input increment and state error is minimized,and the weight matrix in MPC controller is adjusted online to achieve the optimal control performance index.In order to verify the effectiveness of this method,the curve trajectory is simulated and tracked.The simulation results show that the algorithm can adaptively adjust the weighting matrix of MPC controller and improve the tracking performance of the system.(3)Mobile robot trajectory tracking needs to approach the reference trajectory in space while taking into account the real-time requirements of the control system.However,the classical model predictive control has the defect of large amount of online calculation.In order to meet the real-time requirements,an event triggered MPC controller optimization method for mobile robot trajectory tracking is proposed.The effects of minimum event interval time and disturbance upper bound on tracking performance and computational load are analyzed,and an event triggering mechanism based on adaptive threshold is designed for MPC controller.Simulation results show that this method can reduce the update times of solving the optimization problem and effectively reduce the amount of online calculation without affecting the control performance of the system. |
