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一种改进的紧格式无模型自适应控制方法
引用本文:庞中华,马标,宋文太,刘国平.一种改进的紧格式无模型自适应控制方法[J].控制与决策,2021,36(2):436-442.
作者姓名:庞中华  马标  宋文太  刘国平
作者单位:北方工业大学现场总线技术及自动化北京市重点实验室,北京100144;北京全路通信信号研究设计院集团有限公司安全控制技术研究院,北京100070;武汉大学电气与自动化学院,武汉430072
基金项目:国家自然科学基金项目(61673023,61773144,61690212);北京市自然科学基金项目(4182019);北京市教委基本科研业务费项目(110052971921/026);北方工业大学科技创新工程计划项目(110051360019 XN115);北方工业大学毓杰人才培养计划项目(107051360019XN133/001).
摘    要:针对一类由一般非线性函数描述的离散时间非线性系统,采用等价动态线性化技术,提出一种改进的紧格式无模型自适应控制(iCF-MFAC)方法.iCF-MFAC方法的自适应控制律包含两项:时变比例控制项和时变积分控制项,与只有一项时变积分项的原CF-MFAC方法相比,iCF-MFAC方法具有更好的通用性和灵活性,并能够提供更好的动态控制性能.其次,将iCF-MFAC方法与具有类似控制器结构的基于全格式动态线性化技术的无模型自适应控制方法进行对比分析,在相同控制器参数作用下,iCF-MFAC方法具有更快的输出响应.最后,从理论上证明闭环iCF-MFAC系统的收敛性和稳定性,并分别通过数值仿真和真实实验验证所提出方法的有效性和可行性.

关 键 词:数据驱动控制  无模型自适应控制  非线性系统  紧格式动态线性化

An improved compact form model free adaptive control method
PANG Zhong-hu,MA Biao,SONG Wen-tai,LIU Guo-ping.An improved compact form model free adaptive control method[J].Control and Decision,2021,36(2):436-442.
Authors:PANG Zhong-hu  MA Biao  SONG Wen-tai  LIU Guo-ping
Affiliation:Beijing Key Laboratory of FTA,North China University of Technology,Beijing 100144,China;Institute of Safety Control Technology,CRSC Research & Design Institute Group Co.,Ltd.,Beijing 100070; School of Electrical Engineering and Automation,Wuhan University,Wuhan 430072,China
Abstract:An improved compact format model free adaptive control (iCF-MFAC) method based on an equivalent dynamic linearization technique is proposed for a class of discrete-time nonlinear systems described by a general nonlinear function. The adaptive control law of the iCF-MFAC method consists of two parts: A time-varying proportional control term and a time-varying integral control term. Compared with the corresponding original CF-MFAC method with only a time-varying integral term, the iCF-MFAC method is not only more universal and flexible, but also can provide a better dynamical control performance. In addition, the comparison is also made between the iCF-MFAC method and an MFAC method that has a similar controller structure and is based on a full format dynamic linearization data model. With the same controller parameters, the iCF-MFAC can yield a faster output response. Then, the convergence and stability of the resulting closed-loop iCF-MFAC system are proved through rigorous analysis. Both numerical simulations and practical experiments are carried out to demonstrate the effectiveness and feasibility of the proposed method.
Keywords:data-driven control  model free adaptive control  nonlinear systems  compact form dynamic linearization
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