ASSERVISSEMENTS CONTINUS PDF

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Analysis and Optimization of Systems pp Cite as. We propose to derive a control-system-design-methodology valuable for non-linear continuous-time processes from a stability-analysis-technique based upon the use of vectorial norms [2] [3].

The design problem is considered from the stability viewpoint and the design methodology is parameter-optimization. A major-difficulty in nonlinear system-stability studies lies in the handling of sufficient stability conditions that can be very conservative with respect to the intrinsic stability properties of the system. A key-point of the proposed method consists in the definition of a scalar criterion the negativity of which implies asymptotic stability of the studied control system.

The design-method is thus achieved by minimizing the value of this criterion. The arguments of the stability-criterion consists of both the adjustable parameters and a representation basis in the state-space. The values of former arguments are the real synthesis-objective whereas the latter ones are artificial and are used in order to obtain the least conservative stability conditions as possible with respect to the choosen stability-analysis-theorem [2]. The minimization of the criterion can be helped by the computation of a steepest-descent direction deduced from the simple-eigen-values sensitivity theory.

We propose then to implement this design-methodology by the use of a special class of state-space representations of the studied systems. A numerical example illustrates this last design-method. Unable to display preview. Download preview PDF. Skip to main content. This service is more advanced with JavaScript available. Advertisement Hide. Definition d'une methodologie de conception assistee d'asservissements non lineaires continus par l'utilisation de techniques d'agregation par normes vectorielles.

Abstract We propose to derive a control-system-design-methodology valuable for non-linear continuous-time processes from a stability-analysis-technique based upon the use of vectorial norms [2] [3]. This process is experimental and the keywords may be updated as the learning algorithm improves. This is a preview of subscription content, log in to check access. Google Scholar. DEIF A. Control, Vol. AC, pp. Villeneuve D'Ascq Cedex France.

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