Linear-Quadratic Tracking Control of a Commercial Vehicle Air Brake System

This article proposes to utilize linear-quadratic tracking (LQT) control to reduce the air brake system response time and vehicle stopping distance, and hence, to significantly improve the system performance of a commercial vehicle air brake system equipped with electro-pneumatic proportional valve actuators. The nonlinear dynamic model of the air brake system, consisting of a control actuator (a proportional valve) and braking actuator (the brake chamber), is developed and linearized using the $q$ -Markov COVariance Equivalent Realization ( $q$ -Markov Cover) method in our early work. Based on the linearized dynamic model, an infinite horizon LQT controller is designed along with Kalman state estimation at each linearized operational condition. To apply the LQT control law over a wide operational range to track the target pressure, the designed controller was interpolated between the neighboring controllers to have a control law cover the entire operational range. To validate this control law, the control scheme is implemented into a dSPACE unit and validated through bench tests under different supply and reference pressures. The LQT control performance is also compared with the PID (proportional-integral-derivative) one. The bench test results confirm the effectiveness of the proposed control scheme.

[1]  Shankar C. Subramanian,et al.  Application of PID control to an electro-pneumatic brake system , 2012 .

[2]  Christopher M. Bingham,et al.  Application of fuzzy control algorithms for electric vehicle antilock braking/traction control systems , 2003, IEEE Trans. Veh. Technol..

[3]  Martin Horn,et al.  Development of a wheel slip actuator controller for electric vehicles using energy recuperation and hydraulic brake control , 2011, 2011 IEEE International Conference on Control Applications (CCA).

[4]  Ahmad Saifizul,et al.  Dynamic simulation of brake pedal force effect on heavy vehicle braking distance under wet road conditions , 2016 .

[5]  Han-Shue Tan,et al.  Pneumatic Brake Control for Precision Stopping of Heavy-Duty Vehicles , 2007, IEEE Transactions on Control Systems Technology.

[6]  Chris Manzie,et al.  Electromechanical Brake Modeling and Control: From PI to MPC , 2008, IEEE Transactions on Control Systems Technology.

[7]  Hui Lin,et al.  Iterative learning control of antilock braking of electric and hybrid vehicles , 2005, IEEE Transactions on Vehicular Technology.

[8]  Robert E. Skelton,et al.  Q-Markov Cover Identification Using Pseudo Binary Signals WM 5 = 150 Random , 2004 .

[9]  Zhen Ren,et al.  Integrated System ID and Control Design for an IC Engine Variable Valve Timing System , 2011 .

[10]  Okyay Kaynak,et al.  A Grey System Modeling Approach for Sliding-Mode Control of Antilock Braking System , 2009, IEEE Transactions on Industrial Electronics.

[11]  Tankut Acarman,et al.  Pneumatic brake system modeling for systems analysis , 2000 .

[12]  P Oppenheimer THE DEVELOPMENT OF INTERNATIONAL ANTI-LOCK BRAKING REGULATIONS , 1985 .

[13]  Seibum B. Choi,et al.  Development of an Antilock Brake System for Electric Vehicles Without Wheel Slip and Road Friction Information , 2019, IEEE Transactions on Vehicular Technology.

[14]  Stefano Di Gennaro,et al.  Nonlinear adaptive controller applied to an Antilock Braking System with parameters variations , 2017 .

[15]  Shankar C. Subramanian,et al.  Model-based braking control of a heavy commercial road vehicle equipped with an electropneumatic brake system , 2017 .

[16]  A. G. Butkovskiy,et al.  Optimal control of systems , 1966 .

[17]  Guoming G. Zhu,et al.  Profile Tracking for an Electro-Hydraulic Variable Valve Actuator Using Receding Horizon LQT , 2019, IEEE/ASME Transactions on Mechatronics.

[18]  Frank L. Lewis,et al.  Optimal Tracking Control of Unknown Discrete-Time Linear Systems Using Input-Output Measured Data , 2015, IEEE Transactions on Cybernetics.

[19]  T. P. Newcomb,et al.  Automobile Brakes and Braking Systems , 1975 .

[20]  A. K. M. Mohiuddin,et al.  Electro-hydro-mechanical Braking System for Passenger Vehicle , 2018 .

[21]  Yimin Gao,et al.  Study on the Dynamic Characteristics of Pneumatic ABS Solenoid Valve for Commercial Vehicle , 2007, 2007 IEEE Vehicle Power and Propulsion Conference.

[22]  Vicenç Puig,et al.  Autonomous vehicle control using a kinematic Lyapunov-based technique with LQR-LMI tuning , 2018 .

[23]  Hassan Salarieh,et al.  Path-following in model predictive rollover prevention using front steering and braking , 2017 .

[24]  Yingxu Wang,et al.  A Control-Oriented Linear Parameter-Varying Model of a Commercial Vehicle Air Brake System , 2020, Applied Sciences.

[25]  Vipin Sharma,et al.  Mathematical Model to Evaluate and Optimize the Dynamic Performance of Pneumatic Brake System , 2015 .

[26]  F. Udwadia Optimal tracking control of nonlinear dynamical systems , 2008, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[27]  Shankar C. Subramanian,et al.  A Diagnostic System for Air Brakes in Commercial Vehicles , 2006, IEEE Transactions on Intelligent Transportation Systems.

[28]  Peter R.N. Childs Pneumatics and Hydraulics , 2014 .

[29]  Antonio Jesús Guerra Fernández,et al.  A Novel Electrohydraulic Brake System With Tire–Road Friction Estimation and Continuous Brake Pressure Control , 2016, IEEE Transactions on Industrial Electronics.

[30]  Hongchang Zhang,et al.  Robust Design of a Pneumatic Brake System in Commercial Vehicles , 2009 .

[31]  Jan Lunze Adaptive Cruise Control With Guaranteed Collision Avoidance , 2019, IEEE Transactions on Intelligent Transportation Systems.