Cooperative Control of Coupled Multiagent System of Autonomous Vehicle Chassis Based on Co-DMPC

Four-wheel driving/four-wheel steering vehicle has the advantages of high-speed stability, steering response, and safety, making them perform excellently under various driving conditions. However, it also faces challenges due to complex dynamic couplings, multiple control inputs, and computational burden. To address these problems, this article proposes a multiagent cooperative control architecture based on cooperative distributed model predictive control (Co-DMPC). The article explains the coupling mechanisms between agents by establishing distributed state equations and reduces the control inputs of each controller. It defines predicted trajectories, assumed trajectories, and optimal trajectories for states and control inputs, laying the foundation for the interaction of coupled information between agents. The impact of different agents on global performance indicators is measured by solving the cost coupling optimization problem. Furthermore, the iterative solution approach and the termination conditions address the balance between solution accuracy and computational efficiency. The Lyapunov function direct method is used to prove the asymptotic stability of both local and global systems. This article quantitatively analyzes the influence of weight coefficients on control effects and presents an adaptive weight selection method based on road adhesion coefficient. Compared with centralized control, the proposed method has excellent tracking accuracy, response speed, and stability. Furthermore, the hardware-in-loop (HIL) test also demonstrates the performance of the proposed controller.