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Necessary and sufficient Lyapunov-like conditions for robust nonlinear stabilization

Iasson Karafyllis, Zhong-Ping Jiang (2010)

ESAIM: Control, Optimisation and Calculus of Variations

In this work, we propose a methodology for the expression of necessary and sufficient Lyapunov-like conditions for the existence of stabilizing feedback laws. The methodology is an extension of the well-known Control Lyapunov Function (CLF) method and can be applied to very general nonlinear time-varying systems with disturbance and control inputs, including both finite and infinite-dimensional systems. The generality of the proposed methodology is also reflected upon by the fact that partial...

Necessary Optimality Conditions for a Lotka-Volterra Three Species System

N. C. Apreutesei (2010)

Mathematical Modelling of Natural Phenomena

An optimal control problem is studied for a Lotka-Volterra system of three differential equations. It models an ecosystem of three species which coexist. The species are supposed to be separated from each others. Mathematically, this is modeled with the aid of two control variables. Some necessary conditions of optimality are found in order to maximize the total number of individuals at the end of a given time interval.

Nonlinear diagnostic filter design: algebraic and geometric points of view

Alexey Shumsky, Alexey Zhirabok (2006)

International Journal of Applied Mathematics and Computer Science

The problem of diagnostic filter design is studied. Algebraic and geometric approaches to solving this problem are investigated. Some relations between these approaches are established. New definitions of fault detectability and isolability are formulated. On the basis of these definitions, a procedure for diagnostic filter design is given in both algebraic and geometric terms.

Norm estimates for solutions of matrix equations AX-XB=C and X-AXB=C

Michael I. Gil' (2014)

Discussiones Mathematicae, Differential Inclusions, Control and Optimization

Let A, B and C be matrices. We consider the matrix equations Y-AYB=C and AX-XB=C. Sharp norm estimates for solutions of these equations are derived. By these estimates a bound for the distance between invariant subspaces of matrices is obtained.

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