15 research outputs found
Robustness analysis of Cohen-Grossberg neural network with piecewise constant argument and stochastic disturbances
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
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
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 ādescriptorā 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 Hā 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 meĢmoire de theĢse traite du filtrage et de la commande des systeĢmes non lineĢaires deĢcrits par des eĢquations diffeĢrentielles stochastiques au sens dāItoĢ dont la diffusion est commandeĢe par un bruit qui intervient de manieĢre multiplicative avec lāeĢtat. Ce bruit est un processus de Wiener, aussi appeleĢ mouvement brownien. Lorsque le bruit agit de manieĢre multiplicative avec lāeĢtat dans une eĢquation diffeĢrentielle, il peut stabiliser ou deĢstabiliser le systeĢme, ce qui nāest pas le cas lorsque le bruit intervient de manieĢre additive. Il y a plusieurs types de stabiliteĢ pour les systeĢmes deĢcrits par des eĢquations diffeĢrentielles stochastiques, certaines eĢtant plus pessimistes que dāautres. Dans ce manuscrit, nous avons chercheĢ aĢ relaxer les conditions de stabiliteĢ utiliseĢes dans la litteĢrature en employant la stabiliteĢ exponentielle presque suĢre, aussi appeleĢe stabiliteĢ exponentielle avec une probabiliteĢ de un. Trois domaines principaux sont traiteĢs dans ce manuscrit :(i) syntheĢse dāobservateurs, (ii) commande des systeĢmes stochastiques,(iii) lemme borneĢ reĢel pour les systeĢmes stochastiques algeĢbro-diffeĢrentiels.Un nouveau theĢoreĢme sur la stabiliteĢ exponentielle presque suĢre du point dāeĢquilibre dāune classe de systeĢmes stochastiques non lineĢaires triangulaires est proposeĢ : la stabiliteĢ de lāensemble du systeĢme est assureĢe par la stabiliteĢ de chaque sous-systeĢme consideĢreĢ isoleĢment. La preuve de ce reĢsultat est baseĢe sur la majoration des exposants de Lyapunov. On a montreĢ que le probleĢme du filtrage des systeĢmes stochastiques avec des bruits multiplicatifs en imposant la stabiliteĢ exponentielle presque suĢre de lāerreur dāobservation ne peut pas eĢtre reĢsolu en appliquant les approches de type Lyapunov disponibles dans la litteĢrature. Cette difficulteĢ a eĢteĢ surmonteĢe en proposant dāexploiter la structure triangulaire associeĢe aĢ ce probleĢme de filtrage, ce qui nous a permis de deĢcomposer la syntheĢse de lāobservateur en deux sous-probleĢmes deĢcoupleĢs : (i) deĢmontrer la stabiliteĢ de lāeĢquation diffeĢrentielle stochastique deĢcrivant la dynamique de lāeĢtat aĢ estimer, (ii) stabiliser lāeĢquation diffeĢrentielle stochastique deĢcrivant la dynamique de lāerreur dāobservation. Cette approche est baseĢe sur le nouveau theĢoreĢme sur la stabiliteĢ exponentielle presque suĢre dāune classe de systeĢmes stochastiques non lineĢaires triangulaires et lipschitziens eĢvoqueĢe ci- dessus. Ce reĢsultat a eĢteĢ eĢtendu aux systeĢmes stochastiques non lineĢaires ayant des non lineĢariteĢs de type one-sided Lipschitz. Pour garantir la stabiliteĢ de lāerreur dāobservation, une approche de type polytopique a eĢteĢ proposeĢe avec un formalisme ādescripteurā (ou algeĢbro-diffeĢrentiel). Les reĢsultats preĢsenteĢs ci-dessus ont eĢteĢ eĢtendus aĢ la syntheĢse dāobservateurs robustes en preĢsence dāincertitudes parameĢtriques. Des conditions pour le rejet asymptotique des perturbations intervenant dans une eĢquation diffeĢren- tielle stochastique avec des bruits multiplicatifs ont eĢteĢ proposeĢes. La stabiliteĢ consideĢreĢe est la stabiliteĢ exponentielle presque suĢre. Une borne de lāexposant de Lyapunov permet de garantir le taux de conver- gence vers zeĢro de lāeĢtat du systeĢme. Un correcteur de type bang-bang est syntheĢtiseĢ pour une classe de systeĢmes non lineĢaires stochastiques dans deux cas : (i) par retour dāeĢtat et (ii) par retour de sorties mesureĢes avec un observateur. Le type de stabiliteĢ utiliseĢ est la stabiliteĢ exponentielle presque suĢre. Une version du lemme borneĢ reĢel est eĢlaboreĢe pour les systeĢmes stochastiques algeĢbro-diffeĢrentiels (ou singuliers, ou descripteurs) avec des bruits multiplicatifs. Ce travail a neĢcessiteĢ le deĢveloppement de la formule dāItoĢ dans le cas des eĢquations stochastiques algeĢbro-diffeĢrentielles non lineĢaires. Cette approche a eĢteĢ utiliseĢe pour la syntheĢse dāun correcteur Hā par retour de sorties en utilisant la stabiliteĢ exponentielle en moyenne quadratique. Un observateur pour les systeĢmes stochastiques algeĢbro-diffeĢrentiels non lineĢaires a eĢteĢ proposeĢ avec la stabiliteĢ exponentielle presque suĢre
MATLAB
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
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. [...