Distributed Fault-Tolerant Control Strategy for Virtual Coupling Train System Against Measurement Errors and Loss of Actuator Effectiveness

Virtual coupling technology has been widely concerned due to its potential in improving the operational efficiency of rail transit. To mitigate the effects of measurement error and actuation fault on coordinated train operation, this paper proposes a distributed fault-tolerant control strategy for the virtual coupling train system by the integration of moving horizon estimation (MHE) and model predictive control (MPC). Considering potential faults for virtually coupled trains during operation, a faulty model is developed to capture measurement errors and loss of actuator effectiveness. A fault-tolerant control strategy is designed that consists of two modules, i.e., fault estimation and fault-tolerant control. The MHE method is employed in the fault estimation module to estimate faults by solving a local quadratic optimization problem based on historical data. In the fault-tolerant control module, a reconfigured train tracking control problem is constructed under the MPC framework on the premise of real-time estimation. An accelerated alternating direction method of multipliers algorithm is further designed to embed with the fault-tolerant model predictive controller to calculate the control commands in a distributed manner. Numerical experiments are conducted and demonstrate the effectiveness of the proposed approach.