Model Reduction Design Research Articles

H model reduction design in finite frequency ranges for discrete-time Takagi-Sugeno fuzzy systems

This paper addresses the problem of H∞ model reduction design in finite frequency ranges for discrete-time nonlinear systems. With the aid of the generalised Kalman-Yakubovich-Popov (gKYP) lemma, the Lyapunov theory, and some matrix inequality techniques, sufficient conditions for the finite frequency model reduction problem are derived. The design conditions are given in terms of sufficient parameter-dependent linear matrix inequalities that can be solved through relaxations based on semi-definite programming. The advantages of the proposed approach are illustrated through numerical examples and comparisons with other available techniques.

H<SUB align="right">∞ model reduction design in finite frequency ranges for discrete-time Takagi-Sugeno fuzzy systems

This paper addresses the problem of H∞ model reduction design in finite frequency ranges for discrete-time nonlinear systems. With the aid of the generalised Kalman-Yakubovich-Popov (gKYP) lemma, the Lyapunov theory, and some matrix inequality techniques, sufficient conditions for the finite frequency model reduction problem are derived. The design conditions are given in terms of sufficient parameter-dependent linear matrix inequalities that can be solved through relaxations based on semi-definite programming. The advantages of the proposed approach are illustrated through numerical examples and comparisons with other available techniques.

Finite frequency model reduction for 2-D fuzzy systems in FM model

This paper deals with the problem ofH∞model reduction for two-dimensional (2D) discrete Takagi-Sugeno (T-S) fuzzy systems described by Fornasini-Marchesini local state-space (FM LSS) models, over finite frequency (FF) domain. New design conditions guaranteeing the FFH∞model reduction are established in terms of Linear Matrix Inequalities (LMIs). To highlight the effectiveness of the proposedH∞model reduction design, a numerical example is given.

Robust over finite frequency ranges H∞ model reduction for uncertain 2D continuous systems

This paper deals with the problem of robust H∞ model reduction for two-dimensional (2D) continuous systems described by Roesser model with polytopic uncertainties, over finite frequency (FF) domain. The problem to be solved in the paper is to find a reduced-order model such that the approximation error system is asymptotically stable, which is able to approximate the original continuous systems system with comparatively small and minimised H∞ performance when frequency ranges of noises are known beforehand. Via the use of the generalised Kalman Yakubovich Popov (gKYP) lemma, homogeneous polynomially parameter-dependent matrices, Finsler's lemma and we introduce many slack matrices, sufficient conditions for the existence of H∞ model reduction for different FF ranges are proposed and then unified in terms of solving a set of linear matrix inequalities (LMIs). To highlight the effectiveness of the proposed H∞ model reduction design, two illustrative examples are given.