15 research outputs found

    Robustness analysis of Cohen-Grossberg neural network with piecewise constant argument and stochastic disturbances

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    Robustness of neural networks has been a hot topic in recent years. This paper mainly studies the robustness of the global exponential stability of Cohen-Grossberg neural networks with a piecewise constant argument and stochastic disturbances, and discusses the problem of whether the Cohen-Grossberg neural networks can still maintain global exponential stability under the perturbation of the piecewise constant argument and stochastic disturbances. By using stochastic analysis theory and inequality techniques, the interval length of the piecewise constant argument and the upper bound of the noise intensity are derived by solving transcendental equations. In the end, we offer several examples to illustrate the efficacy of the findings

    Discrete Time Systems

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    Discrete-Time Systems comprehend an important and broad research field. The consolidation of digital-based computational means in the present, pushes a technological tool into the field with a tremendous impact in areas like Control, Signal Processing, Communications, System Modelling and related Applications. This book attempts to give a scope in the wide area of Discrete-Time Systems. Their contents are grouped conveniently in sections according to significant areas, namely Filtering, Fixed and Adaptive Control Systems, Stability Problems and Miscellaneous Applications. We think that the contribution of the book enlarges the field of the Discrete-Time Systems with signification in the present state-of-the-art. Despite the vertiginous advance in the field, we also believe that the topics described here allow us also to look through some main tendencies in the next years in the research area

    Filtrage et commande basĆ©e sur un observateur pour les systĆØmes stochastiques

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    This thesis deals with the filtering and control of nonlinear systems described by ItoĢ‚ stochastic differential equations whose diffusion is controlled by a noise which is multiplied with the state vector. The noise is a Wiener process, also known as Brownian motion. When the noise is multiplied with the state in a differential equation, it can stabilize or destabilize the system, which is not the case when the noise occurs additively with respect to the state. In addition, there are several types of stability for the systems described by stochastic differential equations, some being more conservative than others. In this manuscript, the goal is to relax the conditions of stability used in the literature using the almost sure exponential stability, also called exponential stability with probability equal to one. Three main fields are treated in this manuscript :(i) observers synthesis, (ii) stability and stabilization of stochastic systems, (iii) bounded real lemma for stochastic algebro-differential systems.A new theorem on the almost sure exponential stability of the equilibrium point of a class of triangular nonlinear stochastic systems is proposed : the stability of the whole system is ensured by the stability of each decoupled subsystem. The proof of this result is based on the boundedness of the Lyapunov exponents. It was shown that the problem of filtering of stochastic systems with multiplicative noises by imposing the almost sure exponential stability of the observation error can not be solved by using the Lyapunov type approaches available in the literature. This difficulty was overcome by using the triangular structure, associated with this filtering problem, which allows to split the original observer design problem into two decoupled subproblems : (i) demonstrate the stability of the stochastic differential equation describing the dynamics of the state to be estimated, (ii) stabilize the stochastic differential equation describing the dynamics of the observation error. This approach is based on the new theorem on the almost sure exponential stability of a class of Lipschitz triangular nonlinear stochastic systems mentioned above. This has been extended to nonlinear stochastic systems with one-sided Lipschitz nonlinearities. To ensure the stability of the observation error, a polytopic approach was proposed with a ā€œdescriptorā€ formalism (or algebro-differential). The results presented above have been extended to the synthesis of robust observers in the presence of parametric uncertainties. Conditions for asymptotic rejection of perturbations occurring in a stochastic differential equation with multiplicative noises have been proposed. The considered stability is the almost sure exponential one. A bound of the Lyapunov exponent ensures the almost sure convergence rate to zero for the state of the system. A bang-bang control law is synthesized for a class of stochastic nonlinear systems in two cases : (i) state feedback and (ii) measured output feedback with an observer. The used stability is the almost sure exponential one. A version of the bounded real lemma is developed for stochastic algebro-differential systems (also called singular systems or descriptor systems) with multiplicative noises. This work required the development of ItoĢ‚ formula in the case of nonlinear stochastic algebro-differential equations. This approach has been used for the synthesis of an Hāˆž measured output feedback control law with the exponential mean square stability. An observer for nonlinear stochastic algebro-differential systems was proposed using the almost sure exponential stability.Ce meĢmoire de theĢ€se traite du filtrage et de la commande des systeĢ€mes non lineĢaires deĢcrits par des eĢquations diffeĢrentielles stochastiques au sens dā€™ItoĢ‚ dont la diffusion est commandeĢe par un bruit qui intervient de manieĢ€re multiplicative avec lā€™eĢtat. Ce bruit est un processus de Wiener, aussi appeleĢ mouvement brownien. Lorsque le bruit agit de manieĢ€re multiplicative avec lā€™eĢtat dans une eĢquation diffeĢrentielle, il peut stabiliser ou deĢstabiliser le systeĢ€me, ce qui nā€™est pas le cas lorsque le bruit intervient de manieĢ€re additive. Il y a plusieurs types de stabiliteĢ pour les systeĢ€mes deĢcrits par des eĢquations diffeĢrentielles stochastiques, certaines eĢtant plus pessimistes que dā€™autres. Dans ce manuscrit, nous avons chercheĢ aĢ€ relaxer les conditions de stabiliteĢ utiliseĢes dans la litteĢrature en employant la stabiliteĢ exponentielle presque suĢ‚re, aussi appeleĢe stabiliteĢ exponentielle avec une probabiliteĢ de un. Trois domaines principaux sont traiteĢs dans ce manuscrit :(i) syntheĢ€se dā€™observateurs, (ii) commande des systeĢ€mes stochastiques,(iii) lemme borneĢ reĢel pour les systeĢ€mes stochastiques algeĢbro-diffeĢrentiels.Un nouveau theĢoreĢ€me sur la stabiliteĢ exponentielle presque suĢ‚re du point dā€™eĢquilibre dā€™une classe de systeĢ€mes stochastiques non lineĢaires triangulaires est proposeĢ : la stabiliteĢ de lā€™ensemble du systeĢ€me est assureĢe par la stabiliteĢ de chaque sous-systeĢ€me consideĢreĢ isoleĢment. La preuve de ce reĢsultat est baseĢe sur la majoration des exposants de Lyapunov. On a montreĢ que le probleĢ€me du filtrage des systeĢ€mes stochastiques avec des bruits multiplicatifs en imposant la stabiliteĢ exponentielle presque suĢ‚re de lā€™erreur dā€™observation ne peut pas eĢ‚tre reĢsolu en appliquant les approches de type Lyapunov disponibles dans la litteĢrature. Cette difficulteĢ a eĢteĢ surmonteĢe en proposant dā€™exploiter la structure triangulaire associeĢe aĢ€ ce probleĢ€me de filtrage, ce qui nous a permis de deĢcomposer la syntheĢ€se de lā€™observateur en deux sous-probleĢ€mes deĢcoupleĢs : (i) deĢmontrer la stabiliteĢ de lā€™eĢquation diffeĢrentielle stochastique deĢcrivant la dynamique de lā€™eĢtat aĢ€ estimer, (ii) stabiliser lā€™eĢquation diffeĢrentielle stochastique deĢcrivant la dynamique de lā€™erreur dā€™observation. Cette approche est baseĢe sur le nouveau theĢoreĢ€me sur la stabiliteĢ exponentielle presque suĢ‚re dā€™une classe de systeĢ€mes stochastiques non lineĢaires triangulaires et lipschitziens eĢvoqueĢe ci- dessus. Ce reĢsultat a eĢteĢ eĢtendu aux systeĢ€mes stochastiques non lineĢaires ayant des non lineĢariteĢs de type one-sided Lipschitz. Pour garantir la stabiliteĢ de lā€™erreur dā€™observation, une approche de type polytopique a eĢteĢ proposeĢe avec un formalisme ā€œdescripteurā€ (ou algeĢbro-diffeĢrentiel). Les reĢsultats preĢsenteĢs ci-dessus ont eĢteĢ eĢtendus aĢ€ la syntheĢ€se dā€™observateurs robustes en preĢsence dā€™incertitudes parameĢtriques. Des conditions pour le rejet asymptotique des perturbations intervenant dans une eĢquation diffeĢren- tielle stochastique avec des bruits multiplicatifs ont eĢteĢ proposeĢes. La stabiliteĢ consideĢreĢe est la stabiliteĢ exponentielle presque suĢ‚re. Une borne de lā€™exposant de Lyapunov permet de garantir le taux de conver- gence vers zeĢro de lā€™eĢtat du systeĢ€me. Un correcteur de type bang-bang est syntheĢtiseĢ pour une classe de systeĢ€mes non lineĢaires stochastiques dans deux cas : (i) par retour dā€™eĢtat et (ii) par retour de sorties mesureĢes avec un observateur. Le type de stabiliteĢ utiliseĢ est la stabiliteĢ exponentielle presque suĢ‚re. Une version du lemme borneĢ reĢel est eĢlaboreĢe pour les systeĢ€mes stochastiques algeĢbro-diffeĢrentiels (ou singuliers, ou descripteurs) avec des bruits multiplicatifs. Ce travail a neĢcessiteĢ le deĢveloppement de la formule dā€™ItoĢ‚ dans le cas des eĢquations stochastiques algeĢbro-diffeĢrentielles non lineĢaires. Cette approche a eĢteĢ utiliseĢe pour la syntheĢ€se dā€™un correcteur Hāˆž par retour de sorties en utilisant la stabiliteĢ exponentielle en moyenne quadratique. Un observateur pour les systeĢ€mes stochastiques algeĢbro-diffeĢrentiels non lineĢaires a eĢteĢ proposeĢ avec la stabiliteĢ exponentielle presque suĢ‚re

    MATLAB

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    A well-known statement says that the PID controller is the "bread and butter" of the control engineer. This is indeed true, from a scientific standpoint. However, nowadays, in the era of computer science, when the paper and pencil have been replaced by the keyboard and the display of computers, one may equally say that MATLAB is the "bread" in the above statement. MATLAB has became a de facto tool for the modern system engineer. This book is written for both engineering students, as well as for practicing engineers. The wide range of applications in which MATLAB is the working framework, shows that it is a powerful, comprehensive and easy-to-use environment for performing technical computations. The book includes various excellent applications in which MATLAB is employed: from pure algebraic computations to data acquisition in real-life experiments, from control strategies to image processing algorithms, from graphical user interface design for educational purposes to Simulink embedded systems

    Dynamical Systems

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    Complex systems are pervasive in many areas of science integrated in our daily lives. Examples include financial markets, highway transportation networks, telecommunication networks, world and country economies, social networks, immunological systems, living organisms, computational systems and electrical and mechanical structures. Complex systems are often composed of a large number of interconnected and interacting entities, exhibiting much richer global scale dynamics than the properties and behavior of individual entities. Complex systems are studied in many areas of natural sciences, social sciences, engineering and mathematical sciences. This special issue therefore intends to contribute towards the dissemination of the multifaceted concepts in accepted use by the scientific community. We hope readers enjoy this pertinent selection of papers which represents relevant examples of the state of the art in present day research. [...
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