Abstract: The present disclosure provides a speed tracking control method and system for a heavy-haul train. According to the present disclosure, a multi-particle unit-displacement model of the train is established and a robust-adaptive active disturbance rejection control method is adopted, so that an error between an actual speed of the train and a target speed is minimized, an anti-interference capacity of the heavy-haul train is improved, and high-precision tracking control over the target speed of the train is realized.

Abstract: The present disclosure provides a method and system for controlling a heavy-haul train based on reinforcement learning. The method includes: obtaining operation state information of a heavy-haul train at a current time point; obtaining a heavy-haul train action of a next time point according to the operation state information of the heavy-haul train at the current time point and a heavy-haul train virtual controller, and sending the heavy-haul train action of the next time point to a heavy-haul train control unit to control operation of the heavy-haul train. The heavy-haul train virtual controller is obtained by training a reinforcement learning network according to operation state data of the heavy-haul train and an expert strategy network; the reinforcement learning network includes one actor network and two critic networks; the reinforcement learning network is constructed according to a soft actor-critic (SAC) reinforcement learning algorithm.

Abstract: The invention discloses a method and a system for state feedback predictive control of a high-speed train based on a forecast error. The method comprises: obtaining a speed prediction model of a high-speed train y ^ k + p = C ? A p ? x k + ? i = 1 p ? C ? A i - 1 ? B ? u k + p - i ; predicting speeds of the train at times k and k+p according to the speed prediction model; obtaining an actual speed output value of the train; determining a speed prediction error at time k according to the prediction speed of the train and the actual speed output value of the train; correcting a prediction speed of the train at time k+p, according to the speed prediction error, to obtain a corrected prediction speed of the train; calculating a control force uk of the train according to uk=??1(p)[yk+p4 ?yk?Kxk+?k]; and applying a control force to the train based on the control force uk.