Passivity-based cruise control of high speed trains

The cruise control problem of high speed trains (HSTs) is revisited in this paper. Despite the ongoing trend of using Lyapunov-based approaches, the concept of passivity is used as the basis of cruise controller design. To begin with, the Euler–Lagrange modeling of longitudinal motion of HST is introduced. Consequently, passivity properties of the system is investigated and it is shown that the system presents a strictly passive input–output map output. This property is utilized to design a controller based on an energy-shaping method. Since the controller benefits from the passivity property of the train, it is structurally simple and computationally efficient while ensuring asymptotic velocity tracking. In addition, as revealed in our robust analysis, the controller is capable of dealing with bounded perturbations. That is to say, boundedness of velocity tracking errors is guaranteed for sufficiently large control feedback gains. The obtained theoretical results have been verified by numerical simulation.

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Adaptive Fault-Tolerant Cruise Control for a Class of High-Speed Trains with Unknown Actuator Failure and Control Input Saturation

Mathematical Problems in Engineering ◽

10.1155/2014/481315 ◽

2014 ◽

Vol 2014 ◽

pp. 1-13 ◽

Cited By ~ 4

Author(s):

Tao Tao ◽

Hongze Xu

Keyword(s):

High Speed ◽

Monotone Mapping ◽

Input Saturation ◽

Fault Detection And Diagnosis ◽

Control Input ◽

Cruise Control ◽

Nonlinear Dynamic Model ◽

High Speed Trains ◽

And Control ◽

Velocity Tracking

This paper investigates the position and velocity tracking control of a class of high-speed trains (HST) with unknown actuator failures (AF) and control input saturation (CIS). Firstly, a nonlinear dynamic model for HST at normal operating status is built. The structure of traction system in HST is analyzed and the corresponding model for HST with unknown AF is presented as well. The type of AF under consideration is that some of the plant inputs are influenced by hopping function. An adaptive model-based fault detection and diagnosis (AMFDD) module is proposed based on immersion and invariance (I&I) method to make decisions on whether a fault has occurred. A new framework to design a monotone mapping is proposed in I&I method, that is,P(x)-monotone. Using on-line obtained fault information, an adaptive law is designed to update the controller parameters to handle unknown AF and CIS in HST simultaneously when some of plant parameters are unknown. Closed-loop stability and asymptotic position and velocity tracking are ensured. Numerical simulations of China Railways High-speed 2 (CRH2) train are provided to verify the effectiveness of the presented scheme.

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Optimal Simultaneous Kinematic, Dynamic and Control Design of High Performance Manipulators Based on Trajectory Pattern Method

Volume 1A: 25th Biennial Mechanisms Conference ◽

10.1115/detc98/mech-5951 ◽

1998 ◽

Author(s):

J. Rastegar ◽

L. Liu ◽

M. Mattice

Keyword(s):

High Speed ◽

High Performance ◽

Optimality Criterion ◽

Control Design ◽

Tracking Errors ◽

Motion Patterns ◽

Trajectory Pattern ◽

And Control ◽

Velocity Tracking ◽

Trajectory Pattern Method

Abstract An optimal simultaneous kinematic, dynamic and control design approach is proposed for high performance computer controlled machines such as robot manipulators. The approach is based on the Trajectory Pattern Method (TPM) and a fundamentally new design philosophy that such machines in general and ultra-high performance machines in particular must only be designed to perform a class or classes of motions effectively. In the proposed approach, given the structure of the manipulator, its kinematic, dynamic and control parameters are optimized simultaneously with the parameters that describe the selected trajectory pattern. In the example presented in this paper, a weighted sum of the norms of the higher harmonics appearing in the actuating torques and the integral of the position and velocity tracking errors are used to form the optimality criterion. The selected optimality criterion should yield a system that is optimally designed to accurately follow the specified trajectory at high speed. Other objective functions can be readily formulated to synthesize systems for optimal performance. The potentials of the developed method and its implementation for generally defined motion patterns are discussed.

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Adaptive active fault-tolerant controller design for high-speed trains subject to unknown actuator faults

Vehicle System Dynamics ◽

10.1080/00423114.2018.1430836 ◽

2018 ◽

Vol 56 (11) ◽

pp. 1717-1733 ◽

Cited By ~ 4

Author(s):

Xue Lin ◽

Hairong Dong ◽

Xiuming Yao ◽

Baigen Cai

Keyword(s):

High Speed ◽

Active Fault ◽

Controller Design ◽

Fault Tolerant ◽

Actuator Faults ◽

High Speed Trains

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Nonlinear Reduced Order Observer Based Controller Design for High-Speed Trains

2017 14th IEEE India Council International Conference (INDICON) ◽

10.1109/indicon.2017.8487921 ◽

2017 ◽

Author(s):

Meera Patel ◽

Bhanu Pratap

Keyword(s):

High Speed ◽

Controller Design ◽

Reduced Order ◽

High Speed Trains ◽

Reduced Order Observer

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Adaptive Model Predictive Control for Cruise Control of High-Speed Trains with Time-Varying Parameters

Journal of Advanced Transportation ◽

10.1155/2019/7261726 ◽

2019 ◽

Vol 2019 ◽

pp. 1-11 ◽

Cited By ~ 4

Author(s):

Xiaokang Xu ◽

Jun Peng ◽

Rui Zhang ◽

Bin Chen ◽

Feng Zhou ◽

...

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

High Speed ◽

Time Varying ◽

Adaptive Model ◽

Cruise Control ◽

Estimated Parameters ◽

High Speed Trains ◽

Adaptive Model Predictive Control ◽

Resistance Coefficients

The cruise control of high-speed trains is challenging due to the presence of time-varying air resistance coefficients and control constrains. Because the resistance coefficients for high-speed trains are not accurately known and will change with the actual operating environment, the precision of high speed train model is lower. In order to ensure the safe and effective operation of the train, the operating conditions of the train must meet the safety constraints. The most traditional cruise control methods are PID control, model predictive control, and so on, in which the high-speed train model is identified offline. However, the traditional methods typically suffer from performance degradations in the presence of time-varying resistance coefficients. In this paper, an adaptive model predictive control (MPC) method is proposed for cruise control of high-speed trains with time-varying resistance coefficients. The adaptive MPC is designed by combining an adaptive updating law for estimated parameters and a multiply constrained MPC for the estimated system. It is proved theoretically that, with the proposed adaptive MPC, the high-speed trains track the desired speed with ultimately bounded tracking errors, while the estimated parameters are bounded and the relative spring displacement between the two neighboring cars is stable at the equilibrium state. Simulations results validate that proposed method is better than the traditional model predictive control.

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