基于改进遗传算法的自抗扰控制器优化设计

针对超空泡航行体受力特征及其航行时具有非线性、时滞与耦合等复杂问题,提出可根据适应度对控制参数进行自适应动态调整的改进遗传算法。通过建立超空泡航行体纵向模型,设计专用自抗扰控制器对其进行控制,并针对控制器参数多、调节困难的问题,改进了自适应遗传算法对其精确优化。最后通过特性仿真,验证了基于改进的自适应算法的自抗扰控制器相比经典自抗扰控制器的优势。仿真结果表明,该自抗扰控制器符合实际需求,具有良好的控制效果。

Improved genetic algorithm based optimization design of active disturbance rejection controller

We present an improved genetic algorithm that can adaptively adjust control parameters based on fitness degree for the force characteristics of supercavitation navigation body and such complicated issues as nonlinearity, time lag and coupling. We construct longitudinal model of supercavitation navigation body, which is controlled by a specific active disturbance rejection controller (ADRC). We further improve adaptive genetic algorithm to precisely optimize it for such issues as mass controller parameters and difficult adjustment. We eventually verify the advantage of the improved ADRC over classical ADRC through simulation. Simulation results show that the improved ADRC satisfies practical requirements and has better control effect.