基于遗传算法的MFAC参数寻优  

Optimizing the Parameters of MFAC Based on the Genetic Algorithm

作　　者：冯增喜[1,2] 李丙辉 张聪 FENG Zeng-xi;LI Bing-hui;ZHANG Cong(School of Building Services Science and Engineering,Xi`an University of Architecture and Technology,Xi'an Shanxi 710055,China;Anhui Key Laboratory Of Intelligent Building and Building Energy Conservation,Anhui Jianzhu University,Hefei Anhui 230022,China)

机构地区：[1]西安建筑科技大学建科学院,陕西西安710055 [2]安徽建筑大学智能建筑与建筑节能安徽省重点实验室,安徽合肥230022

出　　处：《计算机仿真》2021年第3期170-174,共5页Computer Simulation

基　　金：国家重点研发计划项目专题(2017YFC0704104-03);陕西省科技厅专项科研项目(2017JM6106);安徽建筑大学智能建筑与建筑节能安徽省重点实验室2018年度开放课题(IBES2018KF08)。

摘　　要：无模型自适应控制是基于数据驱动,不依赖于被控对象的数学模型,且结构简单,易于实现。目前关于无模型自适应控制器参数寻优的方法较少,给无模型自适应控制的应用带来了极大的不便。针对这种情况,设计了一种基于遗传算法的MFAC控制器参数寻优方法,并在matlab环境下分别以具有非线性、一阶惯性加大滞后、高阶加大滞后特征等3个不同典型被控系统为对象进行了仿真。仿真结果表明,通过遗传算法进行参数寻优后,控制器性能在超调量、防止调节过程振荡方面效果明显改善,证明了上述方法可行性和优越性。The model-free adaptive control,based on the advanced data-driven,does not require the math model of controlled object.It has a simple structure and is easy to implement.At present,there are few methods for optimizing the parameters of MFAC controller,which brings great inconvenience to the application of model-free adaptive control.To solve this problem,Genetic Algorithm was used to optimize the parameters of MFAC controller,and three different controlled systems,with nonlinearity,first-order inertia plus large time delay,three-order plus time delay respectively,were regarded as the controlled objects,which was used for simulation based on Matlab.The simulation results show that the control effect of MFAC controller optimized by Genetic Algorithm is better,which proves the feasibility and superiority of the method.

关 键 词：无模型自适应控制 参数 遗传算法 寻优 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]