Research On Trajectory Tracking Control Of Mobile Robot Based On Neural Network Predictive Control

In recent years,with the rapid development of robot technology,mobile robots have been widely used in industry,agriculture,public service and other fields.Motion control of mobile robot is the premise to complete various tasks,and trajectory tracking control,as an extremely important part of motion control,is the basis for robot to complete all tasks.Therefore,in order to solve the trajectory tracking control problem of mobile robots,two different trajectory tracking Control algorithms will be designed in combination with Feedforward Neural Network(FNN),Recursive Neural Network(RNN)and Model Predictive Control(MPC).The main research contents are as follows:1.The trajectory tracking control problem of mobile robot based on ESN predictive control method is studied.Firstly,Echo State Network(ESN),an improved recursive neural Network,was used to model the mobile robot.Then,the trained model parameters were substituted into the objective function,and a trajectory tracking controller was designed based on the model predictive control principle.The stability of the algorithm was proved based on the Lyapunov stability theorem.Finally,the simulation experiment proves that the trajectory tracking controller designed by combining ESN and model predictive control not only reduces the computational complexity in the process of rolling optimization,but also has a better tracking effect on the reference trajectory.2.The trajectory tracking control problem of mobile robot based on feedforward neural network predictive control method is studied.Firstly,considering the influence of external uncertainties,RBF neural network is used to model the mobile robot model,and the unmodeled error of the mobile robot can be obtained.Then,a trajectory tracking controller based on RBF neural network predictive control is designed in combination with model predictive control principle under constraint conditions,and the stability of the algorithm is proved by Lyapunov stability theorem analysis.Finally,the simulation results show that the controller effectively overcomes the influence of model error and external disturbance and other uncertain factors.Compared with the traditional trajectory tracking control algorithm,the trajectory tracking effect of the controller is better.