Composite Disturbance‐Observer‐Based Control and Control for High Speed Trains with Actuator Faults

Abstract

To guarantee the position and velocity tracking performance of high speed trains (HSTs) with actuator faults, a composite control algorithm consisting of the disturbance‐observer‐based control (DOBC) and ℋ∞ control is proposed. Based on the multiple point‐mass model, the dynamics of HSTs is established by a cascade of carriages which are connected by flexible couplers, during the procedure of which, the running resistance, actuator faults and multiple disturbances are taken into account. The multiple disturbances are composed of two parts, one of which is the ramp resistance due to the track slope, the other is unknown gusts which can be modeled as a harmonic disturbance with time‐varying frequency. The unknown gusts is estimated and rejected via the DOBC methodology, meanwhile, the running resistance and the ramp resistance are attenuated by the ℋ∞ control methodology. According to the Lyapunov stability analysis and LMI‐based algorithms, main results are derived such that the closed‐loop system is asymptotically stable and the desired performance can be guaranteed. Compared with the numeral simulation results with the single ℋ∞ control method, it is demonstrated that the proposed control methodology is more effective and the system has a higher precision of position and velocity tracking.

Finite frequency fault estimation and fault-tolerant control for dynamics of high-speed train based on descriptor systems

“…Totally speaking, the running resistance of the train is composed of basic resistance and additive resistance (Dong et al, 2018). Basic resistance R g consists of aerodynamic drag R a and mechanical rolling resistance R v .…”

“…Unfortunately, in these studies, wind gust is ignored, and fault estimation and FTC are only effective when actuator faults occur. Although some other disturbance-observer-based results have published by regarding wind gust as the disturbance evolved from exogenous system so that better fault estimation and FTC are implemented (Dong et al, 2018; Yao et al, 2018), their researches were only effective in time domain. Moreover, fault estimation and FTC for concurrent actuator and sensor fault are still not considered.…”

Disturbance observer-based fuzzy fault-tolerant control for high-speed trains with multiple disturbances

“…[33,34] However, most of the existing research on automatic train driving technology for high-speed trains relies on the assumption of the single operating state. [35][36][37] In this case, the stabilization problem based on the fuzzy logic model can be addressed. However, for the tracking problem of high-speed trains, when the position and velocity are both regarded as state variables, the above stabilization method based on fuzzy logic is no longer applicable, and the stabilization problem is meaningless at all.…”

Robust nonlinear model predictive control for automatic train operation based on constraint tightening strategy

“…The safe and efficient operation of trains mainly depends on the performance of the automatic train operation (ATO) system [1]. Dozens of control algorithms [2][3][4][5][6] had been used for the ATO controller design during the past few decades, such as PID control, fuzzy control, neural network control, iterative learning control, adaptive control, and H ∞ control. All of the above methods, however, lack the ability to comprehensively consider multiple optimization objectives for the punctuality of train, energy consumption, and passenger comfort, as well as multiple constraints for safe operation that contain actuator saturation, speed limits, and in-train coupling force limits to prevent train decoupling [7].…”