Multi-objective control of vehicle active suspension systems via load-dependent controllers

This paper presents a load-dependent controller design approach to solve the problem of multi-objective control for vehicle active suspension systems by using linear matrix inequalities. A quarter-car model with active suspension system is considered. It is assumed that the vehicle body mass resides in an interval and can be measured online. This approach of designing controllers, whose gain matrix depends on the online available information of the body mass, is based on a parameter-dependent Lyapunov function. Since the parameter-dependent idea is fully exploited, the proposed controller design approach can yield much less conservative results compared with previous approaches that design robust constant controllers in the quadratic framework. The usefulness and the advantages of the proposed controller design methodology are demonstrated via numerical simulations.

[1]  Timothy Gordon,et al.  A Comparison of Adaptive LQG and Nonlinear Controllers for Vehicle Suspension Systems , 1991 .

[2]  R Kashani,et al.  Robust Stability Analysis of LQG-Controlled Active Suspension with Model Uncertainty Using Structured Singular Value, μ, Method , 1992 .

[3]  Youngjin Park,et al.  STOCHASTIC OPTIMAL PREVIEW CONTROL OF AN ACTIVE VEHICLE SUSPENSION , 1999 .

[4]  A. G. Thompson,et al.  An Active Suspension with Optimal Linear State Feedback , 1976 .

[5]  Hong Chen,et al.  A multi-objective control design for active suspensions with hard constraints , 2003, Proceedings of the 2003 American Control Conference, 2003..

[6]  N. M. Boustany,et al.  Reduced Order Design of Active Suspension Control , 1990 .

[7]  D. Hrovat,et al.  Survey of Advanced Suspension Developments and Related Optimal Control Applications, , 1997, Autom..

[8]  Seung-Bok Choi,et al.  VIBRATION CONTROL OF A SEMI-ACTIVE SUSPENSION FEATURING ELECTRORHEOLOGICAL FLUID DAMPERS , 2000 .

[9]  R. S. Sharp,et al.  NEURAL NETWORK LEARNING CONTROL OF AUTOMOTIVE ACTIVE SUSPENSION SYSTEMS , 1999 .

[10]  Péter Gáspár,et al.  Design of Robust Controllers for Active Vehicle Suspension Using the Mixed µ Synthesis , 2003 .

[11]  S. G. Joshi,et al.  OPTIMUM DESIGN OF A PASSIVE SUSPENSION SYSTEM OF A VEHICLE SUBJECTED TO ACTUAL RANDOM ROAD EXCITATIONS , 1999 .

[12]  P. Gahinet,et al.  H∞ design with pole placement constraints: an LMI approach , 1996, IEEE Trans. Autom. Control..

[13]  James Lam,et al.  Non-fragile output feedback H∞ vehicle suspension control using genetic algorithm , 2003 .

[14]  D. Hrovat,et al.  Optimal Active Suspension Design Using Constrained Optimization , 1997 .

[15]  Giampiero Mastinu,et al.  OPTIMAL AND ROBUST DESIGN OF A ROAD VEHICLE SUSPENSION SYSTEM , 1999 .

[16]  Mario A. Rotea,et al.  The generalized H2 control problem , 1993, Autom..

[17]  M. Al-Majed,et al.  Quadratic Synthesis of Active Controls for a Quarter-Car Model , 2001 .

[18]  Huijun Gao,et al.  Delay-dependent robust H∞ and L2-L∞ filtering for a class of uncertain nonlinear time-delay systems , 2003, IEEE Trans. Autom. Control..

[19]  R. S. Sharp,et al.  ON IMPROVING THE PERFORMANCE OF AUTOMOTIVE SEMI-ACTIVE SUSPENSION SYSTEMS THROUGH ROAD PREVIEW , 1998 .

[20]  C. Wang,et al.  Robust energy-to-peak filtering with improved LMI representations , 2003 .

[21]  Pascal Gahinet,et al.  H/sub /spl infin// design with pole placement constraints: an LMI approach , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.

[22]  Jan A. Snyman,et al.  Optimisation of road vehicle passive suspension systems. Part 1. Optimisation algorithm and vehicle model , 2003 .

[23]  Toshio Yoshimura,et al.  An active vertical suspension for track/vehicle systems , 1986 .

[24]  Stephen P. Boyd,et al.  Linear Matrix Inequalities in Systems and Control Theory , 1994 .