γ-Independent H∞-discretization of sampled-data systems by modified fast-sample/fast-hold approximation with fast lifting

This paper is concerned with Hinfin-discretization for analysis and design of sampled-data control systems and provides a new method with an approximation approach called modified fast-sample/fast-hold approximation. By applying the fast-lifting technique, quasi-finite-rank approximation of an infinite-rank operator and then the loop-shifting technique, this new method can discretize the continuous-time generalized plant in a gamma-independent fashion even when the given sampled- data system has a nonzero direct feedthrough term from the disturbance input w to the controlled output z, unlike in the previous study. With this new method, we can obtain both the upper and lower bounds of the Zinfin-norm or the frequency response gain of any sampled-data systems regardless of the existence of nonzero D11. Furthermore, the gap between the upper and lower bounds can be bounded with the approximation parameter N and is independent of the discrete-time controller. This feature is significant in applying the new method especially to control system design, and this study indeed has a very close relationship to the recent progress in the study of control system analysis/design via noncausal linear periodically time-varying scaling. We demonstrate the effectiveness of the new method through a numerical example.

[1]  E. Rosenwasser,et al.  Computer Controlled Systems: Analysis and Design with Process-orientated Models , 2000 .

[2]  B. Anderson,et al.  Optimal control: linear quadratic methods , 1990 .

[3]  Hiroaki Umeda,et al.  Robust stability analysis of sampled-data systems with noncausal periodically time-varying scaling: Optimization of scaling via approximate discretization and error bound analysis , 2007, 2007 46th IEEE Conference on Decision and Control.

[4]  Bassam Bamieh,et al.  A general framework for linear periodic systems with applications to H/sup infinity / sampled-data control , 1992 .

[5]  Gilead Tadmor,et al.  H ∞ optimal sampled-data control in continuous time systems , 1992 .

[6]  Pramod P. Khargonekar,et al.  Frequency response of sampled-data systems , 1996, IEEE Trans. Autom. Control..

[7]  Yutaka Yamamoto,et al.  A function space approach to sampled data control systems and tracking problems , 1994, IEEE Trans. Autom. Control..

[8]  Tomomichi Hagiwara,et al.  Upper and lower bounds of the frequency response gain of sampled-data systems , 2001, Autom..

[9]  Leonid Mirkin,et al.  Computation of the frequency-response gain of sampled-data systems via projection in the lifted domain , 2002, IEEE Trans. Autom. Control..

[10]  Tomomichi Hagiwara,et al.  Frequency response of sampled-data systems , 1996, Autom..

[11]  R. Middleton,et al.  L2-induced norms and frequency gains of sampled-data sensitivity operators , 1998, IEEE Trans. Autom. Control..

[12]  Tomomichi Hagiwara,et al.  Bisection algorithm for computing the frequency response gain of sampled-data systems - infinite-dimensional congruent transformation approach , 2001, IEEE Trans. Autom. Control..

[13]  Brian D. O. Anderson,et al.  Approximation of frequency response for sampled-data control systems , 1999, Autom..

[14]  Hannu T. Toivonen,et al.  Sampled-data control of continuous-time systems with an H∞ optimality criterion , 1992, Autom..

[15]  Pramod P. Khargonekar,et al.  Frequency response of sampled-data systems , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[16]  Hiroaki Umeda,et al.  Modified fast-sample/fast-hold approximation for sampled-data system analysis , 2007, 2007 European Control Conference (ECC).