Adaptive Position Tracking Compensation for High-Speed Trains with Actuator Failures

In this paper, an adaptive failure compensation is proposed for high-speed trains with traction system actuator failures to achieve the position tracking. To deal with the time-varying parameters of the train motion dynamics, the piecewise constant model is introduced to describe the train dynamics with variable parameters. For the system with actuator failures, the adaptive controller with the adaptive laws is designed to achieve the position tracking, in the presence of the system piecewise constant parameters and actuator failure parameters which are unknown. Simulation results on a high-speed train model are presented to illustrate the performance of the developed adaptive actuator failure compensation control scheme

Adaptive Compensation of Traction System Actuator Failures for High-Speed Trains

In this paper, an adaptive failure compensation problem is addressed for high-speed trains with longitudinal dynamics and traction system actuator failures. Considered the time-varying parameters of the train motion dynamics caused by time-varying friction characteristics, a new piecewise constant model is introduced to describe the longitudinal dynamics with variable parameters. For both the healthy piecewise constant system and the system with actuator failures, the adaptive controller structure and conditions are derived to achieve the plant-model matching. The adaptive laws are designed to update the adaptive controller parameters, in the presence of the system piecewise constant parameters and actuator failure parameters which are unknown. Based on Lyapunov functions, the closed-loop stability and asymptotic state tracking are proved. Sim-ulation results on a high-speed train model are presented to illustrate the performance of the developed adaptive actuator failure compensation control scheme

Adaptive Actuator Compensation of Position Tracking for High-Speed Trains with Disturbances

In this paper, the adaptive fault compensation prob-lem is investigated for high-speed trains in the presence of time-varying system parameters, disturbances and actuator failures. To deal with the time-varying system parameters, a new time-varying indicator function instead of commonly used 0-1 function, is proposed to model the train dynamics as a piecewise model with unparameterizable time-varying disturbances, which can cover more time variations and help parametrization for adaptation. A backstepping adaptive controller is designed for the healthy system with unknown piecewise model parameters and known piecewise bounds on disturbances. For both the parameterizable and unparameterizable failures, the backstepping adaptive fail-ure compensation with the adaptive laws are derived to achieve the position tracking under the known bound disturbances. The adaptive failure compensation for unknown bounds on disturbances is also discussed under the parameterizable failure. Through introducing the nonlinear damping in the proposed controller, the failure compensation controller is proposed for the model with unparameterizable system parameters to achieve an arbitrary degree of position tracking accuracy. The stability of the corresponding closed-loop system and asymptotic state tracking are proved via Lyapunov direct method, and validated using a high-speed train model

Asymptotical Cooperative Cruise Fault Tolerant Control for Multiple High-speed Trains with State Constraints

This paper investigates the asymptotical cooperative cruise fault tolerant control problem for multiple high-speed trains consisting of multiple carriages in the presence of actuator faults. A distributed state-fault observer utilizing the structural information of faults is designed to achieve asymptotical estimation of states and faults of each carriage. The observer does not rely on choice of control input, and thus it is separated from controller design. Based on the estimated values of states and faults, a distributed fault tolerance controller is designed to realize asymptotical cooperative cruise control of trains under the dual constraints of ensuring both position difference and velocity difference of adjacent trains in specified ranges throughout the whole process.Comment: 12 pages, 9 figure

Adaptive Fault-Tolerant Control of A Two-car High-speed Train Model with Inter-car Flexible Link and Traction Actuator Failures

This paper studies the adaptive fault-tolerant tracking control problem for the high-speed trains with intercar flexible link and traction actuator failures. This study is focused on a benchmark model which, as a main dynamic unit of the CRH (China Railway High-speed) train, is a two-car dynamic system with a flexible link between two cars, for which the input acts on the second car and the output is the speed of the first car. This model is under parameter uncertainties and subject to uncertain actuator failures. For such an underactuated system, to ensure the first car tracking a desired speed trajectory, a coordinate transformation method is employed to decompose the system model into a control dynamics subsystem and a zero dynamics subsystem. Stability analysis is conducted to show that such a zero dynamic system is Lyapunov stable and is partially input-to-state stable. An adaptive fault-tolerant control scheme is developed which is able to ensure the closedloop system signal boundedness and desired speed tracking, in the presence of the unknown system parameters and actuator failures. Simulation results from a realistic train dynamic model are presented to verify the desired adaptive control system performance

Adaptive Control Design and Evaluation for Multibody High-speed Train Dynamic Models

In this paper, the adaptive tracking control problem is investigated for multibody high-speed train dynamic model in the presence of unknown parameters, which is an open adaptive control problem. A 4-car train unit model with input signals acting on the 2nd and 3rd cars and output signals being the speeds of the 1st and 3rd cars is chosen as a benchmark model, in which the aerodynamic resistance force is also considered. To handel the nonlinear term, the feedback linearization method is employed to decompose the system into a control dynamics subsystem and a zero dynamics subsystem. A new and detailed stability analysis is conducted to show that such a zero dynamic system is Lyapunov stable and is also partially input-to-state stable under the condition that the speed error between the 1st and 3rd cars is exponentially convergent (to be ensured by a nominal controller) or belongs to the L1 signal space (to be achieved by a properly designed adaptive controller). The system configuration leads to a relative degree 1 subsystem and a relative degree 2 subsystem, for which different feedback linearization-based adaptive controllers and their nominal versions are developed to ensure the needed stabilization condition, the desired closed-loop system signal boundedness and asymptotic output speed tracking. Detailed closed-loop system stability and tracking performance analysis are given for the new control schemes. Simulation results from a realistic train dynamic model are presented to verify the desired adaptive control system performance

Adaptive Fault-Tolerant Sliding-Mode Control for High-Speed Trains with Actuator Faults and Uncertainties

In this paper, a novel adaptive fault-tolerant sliding mode control scheme is proposed for high-speed trains, where the longitudinal dynamical model is focused, and the disturbances and actuator faults are considered. Considering the disturbances in traction force generated by the traction system, a dynamic model with actuator uncertainties modelled as input distribution matrix uncertainty is established. Then, a new sliding-mode controller with design conditions is proposed for the healthy train system, which can drive the tracking error dynamical system to a pre-designed sliding surface in finite time and maintain the sliding motion on it thereafter. In order to deal with the actuator uncertainties and unknown faults simultaneously, the adaptive technique is combined with the fault-tolerant sliding mode control design together to guarantee that the asymptotical convergence of the tracking errors is achieved. Furthermore, the proposed adaptive fault-tolerant sliding-mode control scheme is extended to the cases of the actuator uncertainties with unknown bounds and the unparameterized actuator faults. Finally, case studies on a real train dynamic model are presented to explain the developed fault-tolerant control scheme. Simulation results show the effectiveness and feasibility of the proposed method

Observer Based Traction/Braking Control Design for High Speed Trains Considering Adhesion Nonlinearity

Train traction/braking control, one of the key enabling technologies for automatic train operation, literally takes its action through adhesion force. However, adhesion coefficient of high speed train (HST) is uncertain in general because it varies with wheel-rail surface condition and running speed; thus, it is extremely difficult to be measured, which makes traction/braking control design and implementation of HSTs greatly challenging. In this work, force observers are applied to estimate the adhesion force or/and the resistance, based on which simple traction/braking control schemes are established under the consideration of actual wheel-rail adhesion condition. It is shown that the proposed controllers have simple structure and can be easily implemented from real applications. Numerical simulation also validates the effectiveness of the proposed control scheme

A novel iterative learning approach for tracking control of high-speed trains subject to unknown time-varying delay

In this article, a novel iterative learning control scheme is proposed for high-speed trains, aiming to track the desired reference displacement and velocity, where the Krasovskii function is constructed to compensate for the negative influence of unknown time-varying speed delays. The main feature of the proposed approach is that the hyperbolic tangent function and the command filter are integrated into the learning controller to overcome the singularity problem that may occur during the control process and relax the requirement for the derivability of the desired velocity. The stability of control system is strictly proved through establishing the composite energy function, and the effectiveness is confirmed via numerical simulations. Compared with the existing works, the merits of the proposed control scheme lie in that more general nonlinear uncertainties are imposed on the dynamic model of train instead of the Lipschitz condition, and the reference acceleration assigned by the railway department is not required

Position Error Compensation via a Variable Reluctance Sensor Applied to a Hybrid Vehicle Electric Machine

In the automotive industry, electromagnetic variable reluctance (VR) sensors have been extensively used to measure engine position and speed through a toothed wheel mounted on the crankshaft. In this work, an application that already uses the VR sensing unit for engine and/or transmission has been chosen to infer, this time, the indirect position of the electric machine in a parallel Hybrid Electric Vehicle (HEV) system. A VR sensor has been chosen to correct the position of the electric machine, mainly because it may still become critical in the operation of HEVs to avoid possible vehicle failures during the start-up and on-the-road, especially when the machine is used with an internal combustion engine. The proposed method uses Chi-square test and is adaptive in a sense that it derives the compensation factors during the shaft operation and updates them in a timely fashion