摘要
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。
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 con- vergence 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 per- formance index following the principle separation. This method was tested by an example for the design of a superheated steam tempera- ture 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.
出处
《控制工程》
CSCD
北大核心
2012年第2期286-289,共4页
Control Engineering of China
基金
国家自然科学基金(10971045)
关键词
自抗扰控制器
免疫遗传算法
参数优化
过热汽温控制
auto-disturbance-rejection-control
immune genetic algorithm
parameter optimization
superheated steam temperature con-trol
