基于FHM模型的非线性网络化控制系统H_∞优化控制  

FHM MODEL-BASED H_∞ OPTIMAL CONTROL OF NONLINEAR NETWORKED CONTROL SYSTEMS

作　　者：芮万智[1] 江汉红[1] 刘亮[1] 

机构地区：[1]海军工程大学电气与信息工程学院,武汉430033

出　　处：《系统科学与数学》2015年第10期1161-1167,共7页Journal of Systems Science and Mathematical Sciences

基　　金：国家重点基础研究发展计划973项目(2013CB035601)资助课题

摘　　要：研究了一类具有随机网络诱导时延,数据包丢失和扰动的网络化控制系统H_∞优化控制问题.针对一类非线性被控对象,基于状态反馈控制器,建立了网络化模糊双曲正切混杂系统模型.根据Lyqpunov稳定性理论,给出了系统可实现γ-次优H_∞镇定的充分条件和控制器优化参数的获取方法.仿真算例利用神经网络算法和线性矩阵不等式工具箱,完成了模型参数的辨识与最优扰动衰减度的求取,证明了分析方法和结果的有效性.H∞ optimal control of a class of networked control systems （NCS） with random network-induced delays, packet dropout and disturbance are studied in this paper. Based on state-feedback controller, NCS with nonlinear object is described by a hybrid fuzzy hyperbolic model. The sufficient condition for γ-suboptimum H∞ stabilization of the system, and approach to optimize the controller parameters are derived by making use of Lyapunov theory. Neural network algorithm and linear matrix inequality toolbox are utilized to obtain the identified parameters and optimal attenuation degree in a simulation example, which demonstrates the effectiveness of the proposed method and result.

关 键 词：网络控制系统 模糊双曲正切模型 线性矩阵不等式 神经网络算法 参数辨识. 

分 类 号：O231[理学—运筹学与控制论]