An SOS-Based Control Lyapunov Function Design for Polynomial Fuzzy Control of Nonlinear Systems

This paper deals with a sum-of-squares (SOS)-based control Lyapunov function (CLF) design for polynomial fuzzy control of nonlinear systems. The design starts with exactly replacing (smooth) nonlinear systems dynamics with polynomial fuzzy models, which are known as universal approximators. Next, global stabilization conditions represented in terms of SOS are provided in the framework of the CLF design, i.e., a stabilizing controller with nonparallel distributed compensation form is explicitly designed by applying Sontag\u27s control law, once a CLF for a given nonlinear system is constructed. Furthermore, semiglobal stabilization conditions on operation domains are derived in the same fashion as in the global stabilization conditions. Both global and semiglobal stabilization problems are formulated as SOS optimization problems, which reduce to numerical feasibility problems. Five design examples are given to show the effectiveness of our proposed approach over the existing linear matrix inequality and SOS approaches

Shape-independent model predictive control for Takagi-Sugeno fuzzy systems

[EN] Predictive control of TS fuzzy systems has been addressed in prior literature with some simplifying assumptions or heuristic approaches. This paper presents a rigorous formulation of the model predictive control of TS systems, so that results are valid for any membership value (shape-independent) with a suitable account of causality (control can depend on current and past memberships and state). As in most fuzzy control results, a family of progressively better controllers can be obtained by increasing Polya-related complexity parameters, generalising over prior proposals. (C) 2017 Elsevier Ltd. All rights reserved.The authors are grateful to the financial support of Spanish Ministry of Economy and European Union, grant DPI2016-81002-R (AEI/FEDER, UE), and grant P11B2015-36 (Universitat Jaume I).Ariño-Latorre, CV.; Querol-Ferrer, A.; Sala, A. (2017). Shape-independent model predictive control for Takagi-Sugeno fuzzy systems. Engineering Applications of Artificial Intelligence. 65:493-505. https://doi.org/10.1016/j.engappai.2017.07.011S4935056

Nouveaux schémas de commande et d'observation basés sur les modèles de Takagi-Sugeno

This thesis addresses the estimation and controller design for continuous-time nonlinear systems. The methodologies developed are based on the Takagi-Sugeno (TS) representation of the nonlinear model via the sector nonlinearity approach. All strategies intend to get more relaxed conditions.The results presented for controller design are split in two parts. The first part is about standard TS models under control schemes based on: 1) a quadratic Lyapunov function (QLF); 2) a fuzzy Lyapunov function (FLF); 3) a line-integral Lyapunov functions (LILF); 4) a novel non-quadratic Lyapunov functional (NQLF). The second part concerns to TS descriptor models. Two strategies are proposed: 1) within the quadratic framework, conditions based on a general control law and some matrix transformations; 2) an extension to the nonquadratic approach based on a line-integral Lyapunov function (LILF) using non-PDC control law schemes and the Finsler’s Lemma; this strategy offers parameter-dependent linear matrix inequality (LMI) conditions instead of bilinear matrix inequality (BMI) constraints for second-order systems. On the other hand, the problem of the state estimation for nonlinear systems via TS models is also addressed considering: a) the particular case where premise vectors are based on measured variables and b) the general case where premise vectors can be based on unmeasured variables. Several examples have been included to illustrate the applicability of the obtained results.Cette thèse aborde l'estimation et la conception de commande de systèmes non linéaires à temps continu. Les méthodologies développées sont basées sur la représentation Takagi-Sugeno (TS) du modèle non linéaire par l'approche du secteur non-linéarité. Toutes les stratégies ont l'intention d'obtenir des conditions plus détendu. Les résultats présentés pour la conception de commande sont divisés en deux parties. La première partie est environ sur les modèles TS standard au titre des schémas de commande basés sur: 1) une fonction de Lyapunov quadratique (QLF); 2) une fonction de Lyapunov floue (FLF); 3) une fonction de Lyapunov intégrale de ligne (LILF); 4) un nouveau fonctionnelle de Lyapunov non-quadratique (NQLF). La deuxième partie concerne des modèles TS descripteurs. Deux stratégies sont proposées: 1) dans le cadre quadratique, des conditions basées sur une loi de commande général et quelques transformations de matrices; 2) une extension de l'approche non quadratique basée sur LILF utilisant un schéma de commande non-PDC et le lemme du Finsler; cette stratégie offre conditions sur la forme d’inégalité matricielles linéaires (LMI) dépendant des paramètres au lieu des contraintes sur la forme d’inégalité matricielles bilinéaires (BMI) pour les systèmes de second ordre. D'autre part, le problème de l'estimation de l'état pour les systèmes non linéaires via modèles TS est également abordé considérant: a) le cas particulier où les vecteurs prémisses sont basées sur les variables mesurées et b) le cas général où les vecteurs prémisse peuvent être basés sur des variables non mesurées. Plusieurs exemples ont été inclus pour illustrer l'applicabilité des résultats obtenus

Selective ℋ2 And ℋ∞ Stabilization Of Takagi-sugeno Fuzzy Systems

This paper presents new results concerning the stability analysis and design of state-feedback controllers for continuous-time Takagi-Sugeno (T-S) fuzzy systems via fuzzy Lyapunov functions. The membership functions of the T-S fuzzy systems are modeled in a space that is defined by the Cartesian product of simplexes called a multisimplex. If the time derivatives of the membership functions are bounded, the bounds are used to construct a polytope that models the space of the time derivatives of the membership functions. Linear matrix inequality (LMI) relaxations that are based on polynomial matrices are provided for stability analysis and controller design. Extensions for the design of control laws that minimize upper bounds to ℋ2 and ℋ∞ norms are also given. The main novelty of this method is that it allows one to synthesize control gains, which depends only on some premise variables that are selected by the designer. 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