Static Output-Feedback Control for Vehicle Suspensions: A Single-Step Linear Matrix Inequality Approach

Josep Rubió-Massegú,Josep M Rossell,Francisco Palacios-Quiñonero,Hamid Reza Karimi

doi:10.1155/2013/907056

Abstract

In this paper, a new strategy to design static output-feedback controllers for a class of vehicle suspension systems is presented. A theoretical background on recent advances in output-feedback control is first provided, which makes possible an effective synthesis of static output-feedback controllers by solving a single linear matrix inequality optimization problem. Next, a simplified model of a quarter-car suspension system is proposed, taking the ride comfort, suspension stroke, road holding ability, and control effort as the main performance criteria in the vehicle suspension design. The new approach is then used to design a static output-feedbackH∞controller that only uses the suspension deflection and the sprung mass velocity as feedback information. Numerical simulations indicate that, despite the restricted feedback information, this static output-feedbackH∞controller exhibits an excellent behavior in terms of both frequency and time responses, when compared with the corresponding state-feedbackH∞controller.

Highlights

In recent decades, vehicle suspension systems have been attracting a growing interest
The main objective of this paper is to explore the potential applicability of the new design methodology in the field of vehicle suspensions
To provide a more complete picture of the performance achieved by the proposed static output-feedback controller, in this subsection we present the time response of the quarter-car suspension system to a road disturbance

Summary

Introduction

Vehicle suspension systems have been attracting a growing interest. Much research effort has been devoted to designing different kinds of passive, active, and semiactive vehicle suspensions using a wide variety of control strategies. Some relevant instances of control strategies used in this field are fuzzy control, optimal control, H∞ control, gain scheduling, adaptive control, and model predictive control [1,2,3,4,5]. The development of these control strategies has been closely related to the emergence of computational tools and efficient numerical algorithms, which allow solving complex and sophisticated control problems in a reasonably short time. In the ideal case that the entire state vector is available, many advanced state-feedback controller designs can be formulated as linear matrix inequality (LMI)

Objectives

Results

Conclusion