Online adaptive optimal control of vehicle active suspension systems using single-network approximate dynamic programming
type: Item
instance of: scholarly article
title: Online adaptive optimal control of vehicle active suspension systems using single-network approximate dynamic programming
zbMATH Open document ID: 1426.93281
DOI: 10.1155/2017/4575926
author: Yanyan Li
published in: Mathematical Problems in Engineering
publication date: 2018-11-05T00:00:00Z
review text: Summary: In view of the performance requirements (e.g., ride comfort, road holding, and suspension space limitation) for vehicle suspension systems, this paper proposes an adaptive optimal control method for quarter-car active suspension system by using the approximate dynamic programming approach (ADP). Online optimal control law is obtained by using a single adaptive critic NN to approximate the solution of the Hamilton-Jacobi-Bellman (HJB) equation. Stability of the closed-loop system is proved by Lyapunov theory. Compared with the classic linear quadratic regulator (LQR) approach, the proposed ADP-based adaptive optimal control method demonstrates improved performance in the presence of parametric uncertainties (e.g., sprung mass) and unknown road displacement. Numerical simulation results of a sedan suspension system are presented to verify the effectiveness of the proposed control strategy.
Mathematics Subject Classification ID: 93D21
Mathematics Subject Classification ID: 49L20
Mathematics Subject Classification ID: 93C10
zbMATH DE Number: 6972114
Wikidata QID: Q59147556
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2017/4575926
OpenAlex ID: W2604485348
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description: scientific article; zbMATH DE number 6972114