Model predictive control of an air suspension system with damping multi-mode switching damper based on hybrid model

Abstract This paper presents the hybrid modeling and the model predictive control of an air suspension system with damping multi-mode switching damper. Unlike traditional damper with continuously adjustable damping, in this study, a new damper with four discrete damping modes is applied to vehicle semi-active air suspension. The new damper can achieve different damping modes by just controlling the on-off statuses of two solenoid valves, which makes its damping adjustment more efficient and more reliable. However, since the damping mode switching induces different modes of operation, the air suspension system with the new damper poses challenging hybrid control problem. To model both the continuous/discrete dynamics and the switching between different damping modes, the framework of mixed logical dynamical (MLD) systems is used to establish the system hybrid model. Based on the resulting hybrid dynamical model, the system control problem is recast as a model predictive control (MPC) problem, which allows us to optimize the switching sequences of the damping modes by taking into account the suspension performance requirements. Numerical simulations results demonstrate the efficacy of the proposed control method finally.

[1]  Haobin Jiang Performance Simulation and Testing of Two-levels-damping Adjustable Hydraulic Shock Absorber , 2010 .

[2]  Mohammad Hoseinzadeh,et al.  Vibration suppression of composite plates using smart electrorheological dampers , 2014 .

[3]  Davide Bresolin,et al.  A game-theoretic approach to fault diagnosis and identification of hybrid systems , 2013, Theor. Comput. Sci..

[4]  Nong Zhang,et al.  Direct voltage control of magnetorheological damper for vehicle suspensions , 2013 .

[5]  Alberto Bemporad,et al.  HYSDEL-a tool for generating computational hybrid models for analysis and synthesis problems , 2004, IEEE Transactions on Control Systems Technology.

[6]  Zhengchao Xie,et al.  A Noise-Insensitive Semi-Active Air Suspension for Heavy-Duty Vehicles with an Integrated Fuzzy-Wheelbase Preview Control , 2013 .

[7]  Eduardo F. Camacho,et al.  Model predictive control techniques for hybrid systems , 2010, Annu. Rev. Control..

[8]  Enrong Wang,et al.  Semi-active sliding mode control of vehicle suspension with magneto-rheological damper , 2015 .

[9]  Juan Carlos Ramos,et al.  Development of a thermal model for automotive twin-tube shock absorbers , 2005 .

[10]  Shaohua Wang,et al.  Vehicle height and posture control of the electronic air suspension system using the hybrid system approach , 2016 .

[11]  A. Khajepour,et al.  Analysis and optimization of air suspension system with independent height and stiffness tuning , 2016 .

[12]  Konghui Guo,et al.  A new pneumatic suspension system with independent stiffness and ride height tuning capabilities , 2012 .

[13]  Alberto Bemporad,et al.  Control of systems integrating logic, dynamics, and constraints , 1999, Autom..

[14]  Huba Németh,et al.  Dynamic hybrid model of an electro-pneumatic clutch system , 2013 .

[15]  Yang Ping,et al.  Measurement, simulation on dynamic characteristics of a wire gauze–fluid damping shock absorber , 2006 .

[16]  Xing Xu,et al.  Stability Analysis of Electronically Controlled Air Suspension Ride Height System Based on Center Manifold Method , 2014 .

[17]  Bart De Schutter,et al.  Equivalence of hybrid dynamical models , 2001, Autom..

[18]  Alberto Bemporad,et al.  A bounded-error approach to piecewise affine system identification , 2005, IEEE Transactions on Automatic Control.

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

[20]  Zhang Bin Model of Road Roughness in Time Domain Based on Rational Function , 2009 .

[21]  Javier Nieto,et al.  Air suspension characterisation and effectiveness of a variable area orifice , 2010 .

[22]  Manfred Morari,et al.  Modeling and control of co-generation power plants: a hybrid system approach , 2004, IEEE Trans. Control. Syst. Technol..

[23]  Xuezheng Jiang,et al.  Semi-active control of a vehicle suspension using magneto-rheological damper , 2012 .

[24]  S. Engell Modelling and analysis of hybrid systems , 1998 .

[25]  Alberto Bemporad,et al.  Hybrid Model Predictive Control of a Solar Air Conditioning Plant , 2008, Eur. J. Control.

[26]  Mahdi Tavakoli,et al.  Improved Tracking and Switching Performance of an Electro-Pneumatic Positioning System , 2012 .

[27]  Jun-ichi Imura,et al.  Deterministic finite automata representation for model predictive control of hybrid systems , 2012 .

[28]  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 .

[29]  Alberto Bemporad,et al.  Observability and controllability of piecewise affine and hybrid systems , 2000, IEEE Trans. Autom. Control..

[30]  Manfred Morari,et al.  Hybrid Model Predictive Control of the Step-Down DC–DC Converter , 2008, IEEE Transactions on Control Systems Technology.

[31]  Alberto Bemporad,et al.  An MPC/hybrid system approach to traction control , 2006, IEEE Transactions on Control Systems Technology.

[32]  B. Pregelj,et al.  Hybrid explicit model predictive control of a nonlinear process approximated with a piecewise affine model , 2010 .

[33]  Nong Zhang,et al.  Integrated Seat and Suspension Control for a Quarter Car With Driver Model , 2012, IEEE Transactions on Vehicular Technology.

[34]  Andreas Kugi,et al.  Digitally controlled electrorheological valves and their application in vehicle dampers , 2012 .

[35]  Shaohua Wang,et al.  Damping multi-model adaptive switching controller design for electronic air suspension system , 2015 .