A predictive control method to improve pressure tracking precision and reduce valve switching for pneumatic brake systems

Abstract

Pneumatic brake systems are crucial for the operation of trains. However, due to switching characteristics of on/off solenoid valves, the precise pressure control and low switching activities of valves are difficult to guarantee simultaneously during braking. To address the issue, a hybrid model predictive control (MPC) method is proposed for implementing the multi-objective optimisation in this paper, i.e. the precise pressure tracking and the valve switching reduction. In order to model the hybrid behaviour caused by continuous dynamics of the pressure and discrete features of solenoid valves, the mixed logic dynamical system theory is applied. Then, the braking control problem is recast as a hybrid MPC problem, which jointly optimises the pressure tracking precision and the valve switching. A mixed integer linear program is formulated to solve the MPC problem in an efficient way. Both simulation and experiment results show that the accurate pressure control and low switching activities of valves can be achieved by the proposed method when compared with existing methods.

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

“…However, for a pneumatic system with strong nonlinearity, the transient and steady-state performances of pneumatic systems cannot always be guaranteed with proportional-integral-differential control. Some model-based nonlinear control methods such as sliding mode control [5,6] and model predictive control [7,8] were also proposed to regulate the pressure of electropneumatic actuators. For these methods, the control performance is strongly dependent on the accuracy of the model.…”

“…During the train braking process, it is critical to ensure the pressure control performance, such as improving the tracking speed, reducing the overshoot, and decreasing the steady-state error, so that the rapidity, smoothness, and accuracy of train braking can be guaranteed. In some existing pneumatic pressure control methods for trains, such as sliding mode control [5] and model predictive control [8], it is difficult to achieve the performance constraint quantitatively. The prescribed performance control developed by Bechlioulis et al [16] is a promising method for a performance guarantee.…”

Study on the Pressure Regulation Method of New Automatic Pressure Regulating Valve in the Electronically Controlled Pneumatic Brake Systems in Commercial Vehicles

“…The comparison of the test results shows that feedforward fuzzy PID control can reduce response time and overshoot. Rui Zhang et al [15] established a dynamic model of pneumatic braking system by using the hybrid logic dynamic representation method. A hybrid MPC method was proposed for implementing the multi-objective optimization.…”

Adaptive dual model predictive control for linear systems with parametric uncertainties

“…Then it has been successfully applied in other fields. For example, energy generation [4], resource allocation [5] and flight control [6], pressure control [7]. In practical application, the system models are usually inaccurate.…”