Identification and design of time varying system

In this paper, we analyze system uncertainty of time varying systems caused by identification of the least squares method. The errors between identification models and true systems at each time are investigated and we show that the radius of each corresponding uncertainty can be calculated in a statistical sense. The results are also applied to a design of closed loop systems by the gain scheduling for LPV systems.

[1]  J. Tsitsiklis,et al.  The sample complexity of worst-case identification of FIR linear systems , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[2]  Etsujiro Shimemura,et al.  H∞ Control of Linear Systems with Scheduling Parameter , 1994 .

[3]  A. Packard,et al.  Gain scheduling the LPV way , 1996, Proceedings of 35th IEEE Conference on Decision and Control.

[4]  Hidenori Kimura,et al.  Structure of model uncertainty for a weakly corrupted plant , 1995, IEEE Trans. Autom. Control..

[5]  R. Tempo,et al.  Radially truncated uniform distributions for probabilistic robustness of control systems , 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).

[6]  Michael Athans,et al.  Guaranteed properties of gain scheduled control for linear parameter-varying plants , 1991, Autom..

[7]  J. Tsitsiklis,et al.  The sample complexity of worst-case identification of FIR linear systems , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[8]  Carl N. Nett,et al.  Control oriented system identification: a worst-case/deterministic approach in H/sub infinity / , 1991 .

[9]  A. Packard.  Gain scheduling via linear fractional transformations , 1994 .

[10]  A. Packard,et al.  Control of Parametrically-Dependent Linear Systems: A Single Quadratic Lyapunov Approach , 1993, 1993 American Control Conference.

[11]  H. Chernoff.  A Measure of Asymptotic Efficiency for Tests of a Hypothesis Based on the sum of Observations , 1952 .

[12]  Guoxiang Gu,et al.  Worst Case Identification of Continuous time Systems via Interpolation , 1993, 1993 American Control Conference.