Uncertainty-Estimation-Based Prescribed Performance Pressure Control for Train Electropneumatic Brake Systems

Author:

Zhang Rui1,Xu Zejun1,Yang Yingze2ORCID,Zhu Peidong1ORCID

Affiliation:

1. School of Electronic Information and Electrical Engineering, Changsha University, Changsha 410022, China

2. School of Computer Science and Engineering, Central South University, Changsha 410083, China

Abstract

Fast and precise pressure control for an electropneumatic brake system is essential for ensuring the safe operation of trains. However, the nonlinearity and uncertainties of the system make controller design challenging. This paper proposes a prescribed performance control method integrating an extended state observer to address this issue. A thermodynamical model of the brake cylinder is first built based on the pneumatic characteristics of the braking system, considering multiple modes, coupling effects, and input saturation. Then, an extended state observer is designed to estimate model uncertainty due to temperature variation and disturbances and to achieve online compensation of the model. A feedback control law with a specified prescribed performance function is developed based on the updated thermodynamic model to guarantee the transient and steady-state performance of the pressure control. A parameter adaptive method is also utilized to handle input saturation. The observer’s bounded convergence and stability analysis of the closed-loop control system is given using the Lyapunov theory. Compared experimental results are provided to verify the effectiveness of the proposed method.

Funder

general project of Hunan Natural Science Foundation

Educational Commission of Hunan Province of China

Publisher

MDPI AG

Subject

Control and Optimization,Control and Systems Engineering

Reference25 articles.

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3. Pressure control based on reinforcement learning strategy of the pneumatic relays for an electric-pneumatic braking system;Shan;Proc. Inst. Mech. Eng. Part J. Automob. Eng.,2022

4. Optimal hybrid scheme of dynamic neural network and PID controller based on harmony search algorithm to control a PWM-driven pneumatic actuator position;Mazare;J. Vib. Control,2018

5. Sliding mode pressure controller for an electropneumatic brake: Part II: Parameter identification and controller tests;Luo;Proc. Inst. Mech. Eng. Part J. Syst. Control Eng.,2018

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