引用本文:姜伟,王宏力,陆敬辉,秦伟伟,蔡光斌.连续时间多胞线性变参数系统变增益H∞/H2输出反馈控制[J].控制理论与应用,2016,33(9):1225~1235.[点击复制]
JIANG Wei,WANG Hong-li,LU Jing-hui,QIN Wei-wei,CAI Guang-bin.Gain-scheduled H∞/H2 output feedback controller synthesis for continuous-time polytopic linear parameter varying systems[J].Control Theory and Technology,2016,33(9):1225~1235.[点击复制]
连续时间多胞线性变参数系统变增益H∞/H2输出反馈控制
Gain-scheduled H∞/H2 output feedback controller synthesis for continuous-time polytopic linear parameter varying systems
摘要点击 2922  全文点击 1099  投稿时间:2015-09-19  修订日期:2016-04-14
查看全文  查看/发表评论  下载PDF阅读器
DOI编号  10.7641/CTA.2016.50768
  2016,33(9):1225-1235
中文关键词  H∞控制  H2控制  区域极点配置  线性变参数  主动悬架
英文关键词  H∞ control  H2 control  regional pole placement  linear parameter varying  active suspension
基金项目  国家自然科学基金项目(61304239, 61503391, 61503392), 陕西省自然科学基金项目(2015JQ6213)资助.
作者单位E-mail
姜伟* 火箭军工程大学 yixiantian123456@126.com 
王宏力 火箭军工程大学  
陆敬辉 火箭军工程大学  
秦伟伟 火箭军工程大学  
蔡光斌 火箭军工程大学  
中文摘要
      针对一类同时具有参数不确定性和外界干扰的非线性系统, 提出了一种连续时间多胞线性变参数(LPV)系 统变增益H∞/H2输出反馈控制方法. 首先, 对连续时间多胞LPV系统的变增益混合目标(H∞/H2指标和区域极点约 束)输出反馈控制器综合方法进行了数学描述; 其次, 引入新的结构化松弛矩阵变量和参数依赖Lyapunov函数, 将满 足期望性能的混合目标鲁棒动态输出反馈控制问题转化为线性矩阵不等式框架内的有限维凸优化问题, 进一步降 低了所设计LPV控制器的保守性. 最后, 以四分之一车辆模型主动悬架系统为研究对象进行仿真, 仿真结果验证了 本文控制器的有效性.
英文摘要
      This paper focuses on the problem of gain-scheduled H1/H2 output feedback controller synthesis for continuous-time linear parameter varying (LPV) systems with parameter uncertainty and external disturbance simultaneously. First, the mathematical formulation and control objectives, including the H1/H2 performance and regional pole placement, of gain-scheduled mixed-objective robust dynamic output feedback controller for continuous-time LPV systems are presented. Second, in order to further reduce the conservatism of this algorithm, several slack variables and parameter-dependent Lyapunov functions are employed to the well-established performance conditions. Then the desired gain-scheduled mixed-objective robust dynamic output feedback controllers are reformulated as efficiently tractable finitedimensional convex optimization problem in terms of linear matrix inequalities (LMIs). Finally, numerical examples of a quarter car model with an active suspension are given to illustrate the effectiveness of the proposed methods.