基于扩张状态观测器的列车轨迹跟踪控制及其在CMC环境的测试

Train Trajectory Tracking Control Based on Extended State Observer and Its Simulation Test in CMC Environment

在列车运行过程中,存在着复杂且不确定的外部环境,很难获得阻力的表达式和阻力系数,因此,准确的外部阻力估计直接影响到列车轨迹跟踪精度。设计一种新型的基于扩张状态观测器的列车轨迹跟踪控制算法,将外部阻力和内部干扰扩展为一个新的状态变量,并进行精确估计。采用遗传算法对扩张状态观测器的参数进行优化。最后,在国产CMC芯片的硬件环境下进行测试。测试结果表明,基于扩张状态观测器的控制策略比现有广泛使用的PID算法具有更好的跟踪性能。得出以下结论:所设计控制算法通过补偿各种干扰的影响达到列车位置和速度的精确追踪,具有较强的抗干扰性。

In the process of train operation, it is difficult to obtain the expression and the coefficient of the resistance due to the complex and uncertain external environment. Therefore, the accurate estimation of the external resistance is the key factor to the accuracy of the tracking. Thus, a novel train trajectory tracking control algorithm based on the extended state observer is designed, which extends all kinds of resistances to a new state variable for precise estimation. The genetic algorithm is applied to optimize the parameters of the extended state observer. Finally, test is conducted in home-made hardware environment of CMC chip. The test results show that the control strategy based on the extended state observer has better tracking performance than that of the existing PID algorithm. It is concluded that the proposed control algorithm can achieve accurate position tracking and velocity tracking with strong anti-interference ability.