Trajectory Tracking Control of Emergency Supplies Transportation Robot Based on Koopman Operator and ESO-ET-MPC

The transportation of emergency supplies is of great significance in ensuring national security and responding to sudden disasters. The trajectory tracking control of emergency supplies transportation robot is a key technology to ensure the timeliness of transportation. Based on Koopman operator theory, this paper studies the purely data-driven trajectory tracking control problem of emergency supplies transportation robot by combining extended state observer (ESO) and event-triggered model predictive control (ET-MPC) algorithm. Firstly, a high-dimensional linear model of the robot is established using the Koopman operator. Secondly, design ESO to estimate the disturbances during operation. Thirdly, the ET-MPC is used to optimize the control the trajectory tracking of the emergency supplies transportation robot. Finally, a Carsim/Simulink joint simulation is used to verify the performance of the trajectory tracking controller proposed in this paper. The simulation results show that the model established by Koopman operator theory can achieve the high-precision approximation of the robot; compared with the MPC trajectory tracking controller, the ESO-based ET-MPC (ESO-ET-MPC) trajectory tracking controller improves the tracking accuracy of the robot and reduces the triggering times of the optimization problem.