Robust output feedback control of 2D discrete systems with actuator saturation and time-varying delay

An observer-based dynamic output feedback H∞ controller is proposed for a class of two-dimensional (2D) uncertain discrete systems described by the Roesser model with actuator saturation, time-varying state delay and external disturbances. First, a delay-dependent Lyapunov stability condition is derived in linear matrix inequality (LMI) form which uses the reciprocal convex approach and H∞ disturbance attenuation performance is also analysed. Secondly, a convex hull is adopted to represent the saturation nonlinearity. The H∞ control synthesis for uncertain 2D discrete systems is described by a Roesser model subjected to actuator saturation and external disturbances using an observer-based dynamic output feedback approach. Some practical examples are provided to highlight the usefulness of the presented results.

Stability Analysis of 2D Discrete Linear System Described by the Fornasini-Marchesini Second Model with Actuator Saturation

This paper proposes a novel antiwindup controller for 2D discrete linear systems with saturating controls in Fornasini-Marchesini second local state space (FMSLSS) setting. A Lyapunov-based method to design an antiwindup gain of 2D discrete systems with saturating controls is established. Stability conditions allowing the design of antiwindup loops, in both local and global contexts have been derived. Numerical examples are provided to illustrate the applicability of the proposed method.

Robust Filtering of 2D Roesser Discrete Systems: A Polynomial Approach

The problem of robust filtering is investigated for the class of uncertain two-dimensional (2D) discrete systems described by a Roesser state-space model. The main contribution is a systematic procedure for generating conditions for the existence of a 2D discrete filter such that, for all admissible uncertainties, the error system is asymptotically stable, and the norm of the transfer function from the noise signal to the estimation error is below a prespecified level. These conditions are expressed as parameter-dependent linear matrix inequalities. Using homogeneous polynomially parameter-dependent filters of arbitrary degree on the uncertain parameters, the proposed method extends previous results in the quadratic framework and the linearly parameter-dependent framework, thus reducing its conservatism. Performance of the proposed method, in comparison with that of existing methods, is illustrated by two examples.