Direct voltage control of magnetorheological damper for vehicle suspensions

The paper presents a study on the direct voltage control of a magnetorheological (MR) damper for application in vehicle suspensions. As MR damper dynamics is highly nonlinear, the direct control system design for an MR damper is difficult. Representing an MR damper by a Takagi?Sugeno (TS) fuzzy model enables the linear control theory to be directly applied to design the MR damper controller. In this paper, first the MR damper dynamics is represented by a TS fuzzy model, and then an H? controller that considers the suspension performance requirements and the constraint on the input voltage for the MR damper is designed. Furthermore, considering the case that not all the state variables are measurable in practice, the design of an H? observer with immeasurable premise variables and the design of a robust controller are proposed, respectively. Numerical simulations are used to validate the effectiveness of the proposed approaches.

[1]  S. Shokat,et al.  電界応答性キトサン-ポリ(N,N-ジメチルアクリルアミド)セミIPNゲル膜およびそれらの誘電,熱および膨潤キャラクタリゼーション , 2013 .

[2]  Peter Liu,et al.  Sensorless linear induction motor speed tracking using fuzzy observers , 2011 .

[3]  Felix Weber,et al.  Bouc–Wen model-based real-time force tracking scheme for MR dampers , 2013 .

[4]  Wen Fang Xie,et al.  Optimized Control of Semiactive Suspension Systems Using H $_\infty$ Robust Control Theory and Current Signal Estimation , 2012, IEEE/ASME Transactions on Mechatronics.

[5]  Zushu Li,et al.  A Comparison of Suitable Control Methods for Full Vehicle with Four MR Dampers Part II Controller Synthesis and Road Test Validation , 2009 .

[6]  Wei-Hsin Liao,et al.  Vibration Control of a Suspension System via a Magnetorheological Fluid Damper , 2002 .

[7]  S. Narayanan,et al.  Response of a quarter car model with optimal magnetorheological damper parameters , 2013 .

[8]  Kevin A. Snook,et al.  縦方向電界場中で曲げたPIN-PMN-PT単結晶の強度 , 2011 .

[9]  B. F. Spencer Reliability of Randomly Excited Hysteretic Structures , 1986 .

[10]  Hak-Keung Lam,et al.  Stability Analysis of Fuzzy-Model-Based Control Systems - Linear-Matrix-Inequality Approach , 2011, Studies in Fuzziness and Soft Computing.

[11]  L. Felix-Herran,et al.  Control of a semi-active suspension with a magnetorheological damper modeled via Takagi-Sugeno , 2010, 18th Mediterranean Conference on Control and Automation, MED'10.

[12]  B. Marx,et al.  Brief paper: state estimation of Takagi-Sugeno systems with unmeasurable premise variables , 2010 .

[13]  Kazuo Tanaka,et al.  Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach , 2008 .

[14]  David J. Wagg,et al.  Quasi-active suspension design using magnetorheological dampers , 2011 .

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

[16]  Haiping Du,et al.  Model-based Fuzzy Control for Buildings Installed with Magneto-rheological Dampers: , 2009 .

[17]  Wei-Hsin Liao,et al.  Magnetorheological fluid dampers: a review of parametric modelling , 2011 .

[18]  Charles Poussot-Vassal,et al.  A new semi-active suspension control strategy through LPV technique , 2008 .

[19]  Hui-Wen Tu,et al.  LMI-Based Sensorless Control of Permanent-Magnet Synchronous Motors , 2007, IEEE Transactions on Industrial Electronics.

[20]  Nong Zhang,et al.  Application of evolving Takagi-Sugeno fuzzy model to nonlinear system identification , 2008, Appl. Soft Comput..

[21]  Young-Pil Park,et al.  H8 Control Performance of a Full-Vehicle Suspension Featuring Magnetorheological Dampers , 2002 .

[22]  Seung-Bok Choi,et al.  Human simulated intelligent control of vehicle suspension system with MR dampers , 2009 .

[23]  Shirley J. Dyke,et al.  Semiactive Control Strategies for MR Dampers: Comparative Study , 2000 .

[24]  R. A. Williams,et al.  Automotive Active Suspensions , 1992 .

[25]  Konghui Guo,et al.  Constrained H/sub /spl infin// control of active suspensions: an LMI approach , 2005, IEEE Transactions on Control Systems Technology.

[26]  Mehdi Ahmadian,et al.  Non-dimensionalised closed-form parametric analysis of semi-active vehicle suspensions using a quarter-car model , 2011 .

[27]  Faryar Jabbari,et al.  Actuator Saturation and Control Design for Buildings under Seismic Excitation , 2002 .

[28]  Josep Boada Satellite control with saturating inputs. , 2010 .

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

[30]  Shouhu Xuan,et al.  Inverse neuro-fuzzy MR damper model and its application in vibration control of vehicle suspension system , 2012 .

[31]  Sung Hoon Ha,et al.  Design and vibration control of military vehicle suspension system using magnetorheological damper and disc spring , 2013 .

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

[33]  Abdelhamid Rabhi,et al.  Vehicle dynamics and road geometry estimation using a Takagi-Sugeno fuzzy observer with unknown inputs , 2011, 2011 IEEE Intelligent Vehicles Symposium (IV).

[34]  Shirley J. Dyke,et al.  PHENOMENOLOGICAL MODEL FOR MAGNETORHEOLOGICAL DAMPERS , 1997 .

[35]  H. R. Karimi,et al.  Semiactive Control Methodologies for Suspension Control With Magnetorheological Dampers , 2012, IEEE/ASME Transactions on Mechatronics.

[36]  Yan Shen,et al.  Robust modelling and control of vehicle active suspension with MR damper , 2008 .

[37]  James Lam,et al.  Modelling of a magneto-rheological damper by evolving radial basis function networks , 2006, Eng. Appl. Artif. Intell..

[38]  Jun Yoneyama,et al.  Hinfinity filtering for fuzzy systems with immeasurable premise variables: An uncertain system approach , 2009, Fuzzy Sets Syst..

[39]  P. Khargonekar,et al.  An algebraic Riccati equation approach to H ∞ optimization , 1988 .

[40]  Miao Yu,et al.  Comparative research on semi-active control strategies for magneto-rheological suspension , 2010 .

[41]  Tudor Sireteanu,et al.  Semi-active Suspension Control: Improved Vehicle Ride and Road Friendliness , 2008 .

[42]  G Chen,et al.  MR damper and its application for semi-active control of vehicle suspension system , 2002 .

[43]  James Lam,et al.  Semi-active H∞ control of vehicle suspension with magneto-rheological dampers , 2005 .

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

[45]  H. Metered,et al.  An investigation into the use of neural networks for the semi-active control of a magnetorheologically damped vehicle suspension , 2010 .