Adaptive Neural Network Control for Active Suspension Systems With Time-Varying Vertical Displacement and Speed Constraints

• Published in: IEEE transactions on industrial electronics (1982) 2019-12, Vol.66 (12), p.9458-9466
• Main Authors: Liu, Yan-Jun, Zeng, Qiang, Tong, Shaocheng, Chen, C. L. Philip, Liu, Lei
• Format: Article
• Language: English
• Subjects: Active control; Active suspension systems (ASSs); Adaptation models; Adaptive control; Automobile industry; Automotive bodies; barrier Lyapunov function (BLF); Computer simulation; Displacement; Feedback control; Liapunov functions; Lyapunov methods; Network control; Neural networks; neural networks (NNs); Safety; Stability; Stability analysis; Suspension systems; Time-varying systems; Vehicle dynamics
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2019.2893847

In this paper, an adaptive neural network (NN) control scheme is proposed for a quarter-car model, which is the active suspension system (ASS) with the time-varying vertical displacement and speed constraints and unknown mass of car body. The NNs are used to approximate the unknown mass of car body. It is commonly known that the stability and security of the ASSs will be weakened when the constraints are violated. Thus, the control problem of the time-varying vertical displacement and speed constraints for the quarter-car ASSs is a very important task because of the demand of the handing safety. The time-varying barrier Lyapunov functions are used to guarantee the constraints of the vertical displacement not violated, and it can prove the stability of the closed-loop system. Finally, a simulation example for the ASSs is employed to show the feasibility and rationality of the proposed approach.