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Robust switched controller design for linear continuous-time systems

Ilka A., Veselý P.

Archives of Control Sciences

2015

Vol. 25, no. 4

401--416

In this paper we study a novel approach to the design of a robust switched controller for continuous-time systems described by a novel robust plant model using quadratic stability and multi parameter dependent quadratic stability approaches. In the proposed design procedure with an output feedback a novel quadratic cost function is proposed which allows to obtain different performance dependence on the working points. Finally a numerical examples are investigated.

H-infinity control of discrete-time linear systems constrained in state by equality constraints

Filasová A., Krokavec D.

International Journal of Applied Mathematics and Computer Science

2012

Vol. 22, no. 3

551-560

In this paper, stabilizing problems in control design are addressed for linear discrete-time systems, reflecting equality constraints tying together some state variables. Based on an enhanced representation of the bounded real lemma for discrete-time systems, the existence of a state feedback control for such conditioned stabilization is proven, and an LMI-based design procedure is provided. The control law gain computation method used circumvents generally an ill-conditioned singular design task. The principle, when compared with previously published results, indicates that the proposed method outper forms the existing approaches, guarantees feasibility, and improves the steady-state accuracy of the control. Furthermore, better performance is achieved with essentially reduced design effort. The approach is illustrated on simulation examples, where the validity of the proposed method is demonstrated using one state equality constraint.

Stable output feedback model predictive control design: LMI approach

Vesely V., Bars R.

Archives of Control Sciences

2008

Vol. 18, no. 3

385-394

The paper addresses two design problems dealing with a quadratic stable output/state feedback model predictive control for linear systems without constraints. For the first approach the model predictive control is designed for a N2 state ahead prediction using the Lyapunov function approach with cost function. In the second approach, the one step ahead prediction control is designed using classical LQR state feedback controller approach. By Diophantine matrix equation, the classical state feedback is recalculated to output one step ahead model predictive control. Three examples are given to demonstrate the effectiveness of proposed methods.