基于强跟踪滤波器的改进非线性自适应观测器.pdfVIP

2005 1 Jan. 2005 27 1 Systems Engineering and Electronics Vol27 No1 : 1001506X 2005) 010 11104 1 1 2 柯 晶, 乔谊正 , 钱积新 1山东大学控制科学与工程学院, 山东济南250061; 2浙江大学系统工程研究所, 浙江杭州310027) : 对基于强跟踪滤波器的非线性自适应观测器 nonlinear adaptive observer, NAO) 的收敛性进行了 析, 给 出了NAO 局部渐近收敛的充 条件提出了 一种改进非线性自适应观测器 modif ied nonlinear adaptive observer, MNAO) 算法MNAO 在具有强跟踪特性的同时对输出测量中的坏数据有较强的鲁棒性为了降低对初始误差的敏 感性, 采用 一种强跟踪扩展卡尔曼观测器算法启动MNAO数值仿真示例显示了本方法的有效性 : 非线性观测器; 扩展卡尔曼滤波器; 强跟踪滤波器; 自适应观测器 : O231. 2 : A Modified nonlinear adaptive observer based on strong tracking filter 1 1 2 KE Jing , QIAO Yizheng , QIAN Jixin ( 1. School of Control Science and Engineering, Shandong University, Jinan 250061, China; 2 . Instit te of Systems Engineering , Zhej iang University, Hangz ho 310027, China) Abstract : Convergence of the strong tracking filter based nonlinear adaptive observer NAO) is analyzed and suf ficient conditions for local asymptotic convergence of NAO are established. A modified nonlinear adaptive observer MNAO) is proposed. MNAO is robustn to bad data in output measurements besides its strong tracking properties. To reduce the sensitivity to the initial error , MNAO is initialized by a strong tracking extended Kalman observer algorithm. Numerical simulation example reveals the effectiveness of the method. Key words: nonlinear observer ; extended Kalman filter ; strong tracking filter; adaptive observer