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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。
Aiming at the problem that the parameter of ADRC is not easy to set, a method of parameter optimization based on immune genetic algorithm is proposed. Compared with standard genetic algorithm, immune genetic algorithm introduces immune memory bank and concentration control mechanism, which improves the convergence efficiency and local convergence performance of the algorithm. Considering the dynamic performance of the system and the limiting factors of the control cost in the actual project, the objective function of the performance evaluation of the control system is established. According to the principle of separation, the ADRC controller is designed and its key parameters are optimized by immune genetic algorithm. The method is applied to the variable working condition of the superheated steam temperature control system. The simulation results show that the ADRC controller optimized by the immune genetic algorithm is more adaptable and suitable for the controlled object with a larger range of the model parameters.