Data-Driven Optimal Control for Half-Vehicle Suspension System via Adaptive Dynamic Programming
Hongyang Li, Qinglai Wei · 2022 IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS) · 2022
In this paper, a data-driven optimal control method is provided for the half-vehicle suspension system via adaptive dynamic programming. The main contribution of this paper is that the data-driven adaptive dynamic programming method is applied to the optimal control problem of half-vehicle suspension system, which only requires the input-state data of the system. First, the structure of the half-vehicle suspension system is analyzed, and the optimal control problem is introduced. Next, the model-based adaptive dynamic programming method is provided. Based on the model-based method, a data-driven adaptive dynamic programming method is given. The properties of the provided methods are analyzed. Finally, simulation example is given to show the effectiveness of the data-driven adaptive dynamic programming method.