title: Adaptive control of nonlinear uncertain active suspension systems with prescribed performance.
abstract: This paper proposes adaptive control designs for vehicle active suspension systems with unknown nonlinear dynamics (e.g., nonlinear spring and piece-wise linear damper dynamics). An adaptive control is first proposed to stabilize the vertical vehicle displacement and thus to improve the ride comfort and to guarantee other suspension requirements (e.g., road holding and suspension space limitation) concerning the vehicle safety and mechanical constraints. An augmented neural network is developed to online compensate for the unknown nonlinearities, and a novel adaptive law is developed to estimate both NN weights and uncertain model parameters (e.g., sprung mass), where the parameter estimation error is used as a leakage term superimposed on the classical adaptations. To further improve the control performance and simplify the parameter tuning, a prescribed performance function (PPF) characterizing the error convergence rate, maximum overshoot and steady-state error is used to propose another adaptive control. The stability for the closed-loop system is proved and particular performance requirements are analyzed. Simulations are included to illustrate the effectiveness of the proposed control schemes.
authors.affiliation: Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, P.O. Box 650500, Kunming, China.
authors.forename: Yingbo
authors.initials: Y
authors.lastname: Huang
authors.affiliation: Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, P.O. Box 650500, Kunming, China. Electronic address: najing25@163.com.
authors.forename: Jing
authors.initials: J
authors.lastname: Na
authors.affiliation: Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, P.O. Box 650500, Kunming, China.
authors.forename: Xing
authors.initials: X
authors.lastname: Wu
authors.affiliation: Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, P.O. Box 650500, Kunming, China.
authors.forename: Xiaoqin
authors.initials: X
authors.lastname: Liu
authors.affiliation: Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, P.O. Box 650500, Kunming, China.
authors.forename: Yu
authors.initials: Y
authors.lastname: Guo
keywords: Active suspension system; Adaptive control; Neural networks; Prescribed performance