The problem of the robust and optimal control for uncertain quadratic systems is dealt with in this paper. Resorting to a guaranteed cost approach, this paper proposes a novel control design methodology which enables to find a state feedback controller guaranteeing for the closed-loop system: i) the local asymptotic stability of the zero equilibrium point; ii) the inclusion of a given polytopic region into the domain of attraction of the zero equilibrium point; iii) the satisfaction of a quadratic performance index. The control performance is guaranteed against parametric uncertainties which are assumed to be norm-bounded. This design procedure involves the solution of a Linear Matrix Inequalities (LMIs) optimization problem, which can be efficiently solved via off-the-shelf algorithms. An example, concerning an application of motion control for robotic arms, shows the effectiveness of the proposed methodology.
Guaranteed cost control for uncertain nonlinear quadratic systems / Amato, Francesco; Colacino, Domenico; Cosentino, Carlo; Merola, Alessio. - (2014), pp. 1229-1235. (Intervento presentato al convegno 13th European Control Conference, ECC 2014 tenutosi a Strasbourg Convention and Exhibition Center, Place de Bordeaux, FRANCE nel 2014) [10.1109/ECC.2014.6862287].
Guaranteed cost control for uncertain nonlinear quadratic systems
Amato, Francesco;
2014
Abstract
The problem of the robust and optimal control for uncertain quadratic systems is dealt with in this paper. Resorting to a guaranteed cost approach, this paper proposes a novel control design methodology which enables to find a state feedback controller guaranteeing for the closed-loop system: i) the local asymptotic stability of the zero equilibrium point; ii) the inclusion of a given polytopic region into the domain of attraction of the zero equilibrium point; iii) the satisfaction of a quadratic performance index. The control performance is guaranteed against parametric uncertainties which are assumed to be norm-bounded. This design procedure involves the solution of a Linear Matrix Inequalities (LMIs) optimization problem, which can be efficiently solved via off-the-shelf algorithms. An example, concerning an application of motion control for robotic arms, shows the effectiveness of the proposed methodology.File | Dimensione | Formato | |
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