自抗扰控制器参数的免疫遗传优化及应用

针对自抗扰控制器参数较多不易整定的问题,提出了基于免疫遗传算法的参数优化设计方法。与标准遗传算法相比,免疫遗传算法引入了免疫记忆库和浓度控制机制,提高了算法的收敛效率和局部收敛性能。并且综合考虑系统动态性能和实际工程中控制代价的限制因素建立了控制系统性能评价的目标函数,按照分离性原则进行自抗扰控制器设计并用免疫遗传算法对其关键参数进行寻优。将该方法应用于过热汽温度控制系统的变工况运行,仿真实验结果表明经过免疫遗传算法优化后的自抗扰控制器适应性较强,适用于模型参数变化范围较大的受控对象。

Parameters Optimization and Application of Auto-Disturbance-Rejection-Controller Based on Immune Genetic Algorithm

The Parameter optimization method is proposed based on immune genetic algorithm(IGA) in order to overcome the difficulty in tuning multi parameters of auto-disturbance-rejection-controller(ADRC) suitably.The efficiency of the convergence and local convergence of IGA are improved by using immune memory and concentration control mechanism.An integrated optimum objective function is established on the basis of integral of time multiplied by the absolute value of error criterion by considering the dynamic performance and control cost constraints of the actual project.The ADRC parameters are optimized by IGA to minimize this integrated evaluation performance index following the principle separation.This method was tested by an example for the design of a superheated steam temperature control system with varying operating load.Simulation results show that the controller is adaptable to the variable parameter models.This method can be applied to some processes whose model parameters change in a wide range.