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+pr?yk?Kxk+?k]; and applying a control force to the train based on the control force uk.

Abstract: A speed measurement method, system and apparatus of a medium and low speed maglev train are provided. The method comprises: determining a position of a marked eddy current sensor for each eddy current pulse of each of two eddy current pulse data groups based on the eddy current pulse, distribution data of maglev steel rail sleepers and eddy current sensors; determining a first speed value based on positions of marked eddy current sensors and pulse moments respectively corresponding to two adjacent eddy current pulses; calculating a second speed value based on a first speed value corresponding to an eddy current pulse data group of which pulse moment is ranked ahead in the two eddy current pulse data groups and an acceleration sensing data; calculating a third speed value based on radar sensing data; and fusing the first, second and third speed values to obtain a final speed value.

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.