This paper studies the problem of automatic train operation (ATO) robust nonlinear model predictive control under considering multiple objectives and constraints. After establishing a nonlinear multipoint model with uncertain bounded disturbance, a robust nonlinear model predictive control algorithm to meet the punctuality of train operation and energy consumption for ATO is proposed based on constraint tightening strategy. Moreover, theoretical analysis of the feasibility and stability for the speed loop system are presented. Then, with the objective of reference electromagnetic torque tracking and low switching frequency, a model predictive direct torque control algorithm with one-step delay compensation is proposed. Feasibility of the proposed algorithm is ensured by using deadlock prediction method, and convergence analysis of the torque loop is given simultaneously. Lastly, the effectiveness of these two algorithms are verified by numerical simulation.

中文翻译：

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基于约束收紧策略的列车自动运行鲁棒非线性模型预测控制

本文研究了考虑多目标和多约束条件下的列车自动运行（ATO）鲁棒非线性模型预测控制问题。在建立具有不确定有界扰动的非线性多点模型后，基于约束收紧策略，提出了一种满足列车运行准时性和ATO能耗的鲁棒非线性模型预测控制算法。此外，还对速度环系统的可行性和稳定性进行了理论分析。然后，以参考电磁转矩跟踪和低开关频率为目标，提出了一种具有一步延迟补偿的模型预测直接转矩控制算法。采用死锁预测方法保证了所提算法的可行性，同时给出了转矩环的收敛性分析。最后通过数值仿真验证了这两种算法的有效性。