Identification of Linear Parameter Varying System Using Flexible Least Squares
This paper introduces the flexible least squares (FLS) for the identification problem of linear parameter varying (LPV) system. FLS considers the measurement error (output estimation error) and dynamic error (parameter estimation error) simultaneously and is suitable for dealing with identification of parameter varying system. It is deduced that FLS is algebraically equivalent to the Kalman filter whose stability criterion has been well developed, a stability criterion is built for FLS in a similar way. Finally we apply FLS to the identification of LPV system, simulation results shown its effectiveness.
Linear parameter varying system flexible least squares recursive
Zeng Jiusun Jin Yang Luo Shihua
College of Metrology & Measurement Engineering, China Jiliang University, Hangzhou 310018, China School of Information Management, Jiangxi University of Finance and Economics, Nanchang 330013, Chin
国际会议
The 31st Chinese Control Conference(第三十一届中国控制会议)
合肥
英文
7641-7646
2012-07-01（万方平台首次上网日期，不代表论文的发表时间）