Fuzzy Control for Nonlinear Uncertain Electrohydraulic Active Suspensions With Input Constraint

This paper presents a Takagi-Sugeno (T-S) model-based fuzzy control design approach for electrohydraulic active vehicle suspensions considering nonlinear dynamics of the actuator, sprung mass variation, and constraints on the control input. The T-S fuzzy model is first applied to represent the nonlinear uncertain electrohydraulic suspension. Then, a fuzzy state feedback controller is designed for the obtained T-S fuzzy model with optimized H infin performance for ride comfort by using the parallel-distributed compensation (PDC) scheme. The sufficient conditions for the existence of such a controller are derived in terms of linear matrix inequalities (LMIs). Numerical simulations on a full-car suspension model are performed to validate the effectiveness of the proposed approach. The obtained results show that the designed controller can achieve good suspension performance despite the existence of nonlinear actuator dynamics, sprung mass variation, and control input constraints.

[1]  Huei Peng,et al.  Adaptive robust force control for vehicle active suspensions. , 2004 .

[2]  B. R. Davis,et al.  Technical Note: Force Control in Electrohydraulic Active Suspensions Revisited , 2001 .

[3]  Rui Liu,et al.  A simplified approach to force control for electro-hydraulic systems☆ , 2000 .

[4]  J. N. Yang,et al.  Actuator saturation and control design for buildings under seismic excitation , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[5]  Bor-Sen Chen,et al.  H/sub /spl infin// Fuzzy Control Design for Nonlinear Systems Subject to Actuator Saturation , 2006, 2006 IEEE International Conference on Fuzzy Systems.

[6]  Dae Sung Joo,et al.  Sliding mode neural network inference fuzzy logic control for active suspension systems , 2002, IEEE Trans. Fuzzy Syst..

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

[8]  Hideki Hashimoto,et al.  Trajectory Tracking by TP Model Transformation: Case Study of a Benchmark Problem , 2007, IEEE Transactions on Industrial Electronics.

[9]  M. Saad,et al.  Identification and Real-Time Control of an Electrohydraulic Servo System Based on Nonlinear Backstepping , 2007, IEEE/ASME Transactions on Mechatronics.

[10]  Jian-Shiang Chen,et al.  A self-organizing fuzzy sliding-mode controller design for a class of nonlinear servo systems , 1994, IEEE Trans. Ind. Electron..

[11]  Andrew G. Alleyne,et al.  A practical and effective approach to active suspension control , 2005 .

[12]  An-Chyau Huang,et al.  Adaptive sliding control of active suspension systems with uncertain hydraulic actuator dynamics , 2003 .

[13]  B. R. Davis,et al.  FORCE CONTROL IN ELECTROHYDRAULIC ACTIVE SUSPENSIONS REVISITED , 2001 .

[14]  Yeung Yam,et al.  Case study of the TP-model transformation in the control of a complex dynamic model with structural nonlinearity , 2006, IEEE Transactions on Industrial Electronics.

[15]  Andrew G. Alleyne,et al.  Application of Nonlinear Control Theory to Electronically Controlled Suspensions , 1993 .

[16]  Shiuh-Jer Huang,et al.  Adaptive sliding controller with self-tuning fuzzy compensation for vehicle suspension control , 2006 .

[17]  Rui Liu,et al.  Systematic control of a class of nonlinear systems with application to electrohydraulic cylinder pressure control , 2000, IEEE Trans. Control. Syst. Technol..

[18]  Zongli Lin,et al.  Robust stability analysis and fuzzy-scheduling control for nonlinear systems subject to actuator saturation , 2003, IEEE Trans. Fuzzy Syst..

[19]  Kazuo Tanaka,et al.  Fuzzy control systems design and analysis , 2001 .

[20]  Andrew G. Alleyne,et al.  Nonlinear adaptive control of active suspensions , 1995, IEEE Trans. Control. Syst. Technol..

[21]  R. A. Williams Automotive active suspensions Part 1: Basic principles , 1997 .

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

[23]  Kazuo Tanaka,et al.  A Descriptor System Approach to Fuzzy Control System Design via Fuzzy Lyapunov Functions , 2007, IEEE Transactions on Fuzzy Systems.

[24]  Péter Baranyi,et al.  TP model transformation as a way to LMI-based controller design , 2004, IEEE Transactions on Industrial Electronics.

[25]  G. Feng,et al.  A Survey on Analysis and Design of Model-Based Fuzzy Control Systems , 2006, IEEE Transactions on Fuzzy Systems.

[26]  Huijun Gao,et al.  Improved Hinfinite control of discrete-time fuzzy systems: a cone complementarity linearization approach , 2005, Inf. Sci..

[27]  R. A. Williams Automotive Active Suspensions , 1992 .

[28]  Antonio Sala,et al.  Relaxed LMI conditions for closed-loop fuzzy systems with tensor-product structure , 2007, Eng. Appl. Artif. Intell..

[29]  Rui Liu,et al.  On the Limitations of Force Tracking Control for Hydraulic Servosystems , 1999 .

[30]  Shiuh-Jer Huang,et al.  Adaptive fuzzy controller with sliding surface for vehicle suspension control , 2003, IEEE Trans. Fuzzy Syst..