Optimal robust vehicle motion control under equality and inequality constraints

Abstract

In this paper, a new robust controller is proposed to improve the motion control performance of an autonomous four‐wheel steering vehicle. The vehicle is subject to time‐varying uncertainties caused by parameter perturbation and unmodeled disturbance. First of all, the vehicle motion control problem is modeled as a constraint‐following problem with the goal to drive the vehicle system to follow the given constraints. For safety reasons, inequality constraints are imposed on the lateral displacement of the vehicle. Next, the diffeomorphism mapping method is used to deal with the inequality constraints in the vehicle motion control, and the constrained lateral displacement space is mapped to an unbounded space. On this basis, a new multi‐parameter robust constraint‐following control is designed. Based on Lyapunov stability theory, the approximate constraint tracking performance of the path tracking system is proved. In order to make a trade‐off between the system performance and control cost, a multi‐parameter optimization problem is established, and the optimal robust controller is obtained. Last, the main theoretical results are verified by the Carsim‐Simulink co‐simulations.

Automated Flight Technology for Integral Path Planning and Trajectory Tracking of the UAV

“…In [27], the MPC controller based on Lyapunov input constraint (LMPC) solves the trajectory tracking problem. There are also other methods such as robust control [28], vector field control, and so on. Literature [29] proposes a controller that is robust to cope with the model uncertainty and measurement noise to develop the control accuracy.…”