A Soft-Switching Automatic Control Approach to Cooperative Operation of Multiple Trains With Human Intervention

This paper addresses the cooperative control problem of trains with specific consideration of human interventions in unusual situations where hard handovers on control objectives and safety constraints may occur. To overcome the effects of such discontinuous factors caused by interventions on the smooth operation of trains and avoid drastic changes in the control input, cooperative control policies with soft-switching are constructed based on novel potential energy functions and weighted functions such that, besides achieving consensus among trains for desired velocities and positions, maintaining prescribed tracking distance, collision avoidance is also guaranteed during the state transition process. Furthermore, adaptive approximation and saturation compensation mechanisms are adopted to cope with parameter uncertainties and input saturation. A rigorous proof is provided to demonstrate the correctness of the proposed results theoretically, and numerical experiments are conducted using real operation data to illustrate the theoretical conclusions.