Actuator Failure Compensation-Based Adaptive Control of Active Suspension Systems With Prescribed Performance

• Published in: IEEE transactions on industrial electronics (1982) 2020-08, Vol.67 (8), p.7044-7053
• 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); Actuator failure; Actuators; Adaptation models; Adaptive control; Algorithms; Automotive bodies; Computer simulation; Continuity (mathematics); Control algorithms; Control stability; Control theory; neural network (NN); Neural networks; Nonlinear systems; Passenger comfort; prescribed performance function (PPF); Suspension systems; Suspensions (mechanical systems); Tracking errors; Transient analysis
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2019.2937037

In this article, we study the control problem of the vehicle active suspension systems (ASSs) subject to actuator failure. An adaptive control scheme is presented to stabilize the vertical displacement of the car-body. Meanwhile, the ride comfort, road holding, and suspension space limitation can be guaranteed. In order to overcome the uncertainty, the neural network is developed to approximate the continuous function with the unknown car-body mass. Furthermore, to improve the transient regulation performance of ASSs when the actuator failure occurs, we propose a novel control scheme with the prescribed performance function to characterize the tracking error convergence rate and maximum overshoot in ASSs. Then, the stability of the proposed control algorithm can be proven based on the Lyapunov theorem. Finally, the comparative simulation results of two actuator failure types (i.e., the float fault and the loss of effectiveness fault) are given to demonstrate the effectiveness of the proposed control schemes.