基于混合系统模型预测控制的列车优化运行

为保证列车高效率运行,需要对自动驾驶系统进行高效设计。列车运行过程具有高度非线性化的特性,针对这一特性,通过引入整数变量,建立基于混合系统的列车混合逻辑动态模型,其次考虑列车运行过程的多重约束,通过二次规划求解控制律。同时为了降低控制器计算量,在模型预测控制的基础上引入了阶梯式控制策略。最后利用Matlab仿真软件使其跟踪一条即定曲线,对所提的控制策略进行数值仿真。结果表明,该控制器可以在降低计算量的基础上,保证列车准时高效跟踪既定曲线,当改变控制器参数时,对跟踪效果有较大的影响。仿真结果对本文采用的方法进行了有效验证。

Train Operation Optimization Based on Hybrid System Model Predictive Control

In order to ensure efficient train operation,the automatic driving system needs to be designed efficiently. As train running process is highly nonlinear,a hybrid logic dynamic model of the train based on hybrid system is established by introducing integer variable. Then,the control law is derived from quadratic programming in consideration of the multiple constraints of the train operation process.Meanwhile,to reduce the amount of controller calculation,a stepwise control strategy is introduced based on model predictive control. Finally,the Matlab simulation software is used to track a set of curves and the proposed control strategy is numerically simulated. The results show that the controller can ensure that the train tracks the established curve timely and efficiently on the basis of reduced calculation amount,and the changes of the controller parameters affect the tracking greatly. The simulation results verify the method used in this paper.