<p>In order to design robust controllers, H-infinity synthesis is a common tool to use. The controllers that result from these algorithms are typically of very high order, which complicates implementation. However, if a constraint on the maximum order of the controller is set, that is lower than the order of the plant, the problem is no longer convex and it is then relatively hard to solve. These problems become very complex, even when the order of the system to be controlled is low.</p><p>The approach used in the thesis is based on formulating the constraint on the maximum order of the plant as a polynomial equation. By using the fact that the polynomial is non-negative on the feasible set, the problem is reformulated as an optimization problem where the nonconvex polynomial function is to be minimized over a convex set defined by linear matrix inequalities.</p><p>To solve this optimization problem, two methods have been proposed. The first method is a barrier method and the second one is a method based on a primal-dual framework. These methods have been evaluated on several problems and compared with a well-known method found in the literature. To motivate this choice of method, we have made a brief survey of available methods available for solving the same or related problems.</p><p>The proposed methods emerged as the best methods among the three for finding lower order controllers with the same or similar performance as the full order controller. When the aim is to find the lowest order controller with no worse than +50% increase in the closed loop H-infinity norm, then the three compared methods perform equally well.</p>

In order to design robust controllers, H-infinity synthesis is a common tool to use. The controllers that result from these algorithms are typically of very high order, which complicates implementation. However, if a constraint on the maximum order of the controller is set, that is lower than the order of the plant, the problem is no longer convex and it is then relatively hard to solve. These problems become very complex, even when the order of the system to be controlled is low. The approach used in the thesis is based on formulating the constraint on the maximum order of the plant as a polynomial equation. By using the fact that the polynomial is non-negative on the feasible set, the problem is reformulated as an optimization problem where the nonconvex polynomial function is to be minimized over a convex set defined by linear matrix inequalities. To solve this optimization problem, two methods have been proposed. The first method is a barrier method and the second one is a method based on a primal-dual framework. These methods have been evaluated on several problems and compared with a well-known method found in the literature. To motivate this choice of method, we have made a brief survey of available methods available for solving the same or related problems. The proposed methods emerged as the best methods among the three for finding lower order controllers with the same or similar performance as the full order controller. When the aim is to find the lowest order controller with no worse than +50% increase in the closed loop H-infinity norm, then the three compared methods perform equally well.

This thesis deals with the modern control approaches applicable to speed control of an induction motor. Historical perspective to the control theory and its evolution to the modern control will be presented in a short introduction. Basics of uncertainty modeling are presented along with linear fractional transformation (LFT) representation of an uncertain system. Two different approaches for robust controller synthesis are introduced - H-infinity loopshaping and mixed sensitivity H-infinity synthesis. Theoretical background is presented for both of these methods. Finally the robust controller for induction motor satisfying the control goals is designed using both methods. Design objectives are presented as transfer function weights shaping the sensitivity or complementary sensitivity function to desired shape. Several step responses were simulated to compare H-infinity loopshaping and mixed sensitivity H-infinity controllers with the conventional vector control approach.

When designing controllers with robust performance and stabilization requirements, H-infinity synthesis is a common tool to use. These controllers are often obtained by solving mathematical optimization problems. The controllers that result from these algorithms are typically of very high order, which complicates implementation. Low order controllers are usually desired, since they are considered more reliable than high order controllers. However, if a constraint on the maximum order of the controller is set that is lower than the order of the so-called augmented system, the optimization problem becomes nonconvex and it is relatively difficult to solve. This is true even when the order of the augmented system is low. In this thesis, optimization methods for solving these problems are considered. In contrast to other methods in the literature, the approach used in this thesis is based on formulating the constraint on the maximum order of the controller as a rational function in an equality constraint. Three methods are then suggested for solving this smooth nonconvex optimization problem. The first two methods use the fact that the rational function is nonnegative. The problem is then reformulated as an optimization problem where the rational function is to be minimized over a convex set defined by linear matrix inequalities (LMIs). This problem is then solved using two different interior point methods. In the third method the problem is solved by using a partially augmented Lagrangian formulation where the equality constraint is relaxed and incorporated into the objective function, but where the LMIs are kept as constraints. Again, the feasible set is convex and the objective function is nonconvex. The proposed methods are evaluated and compared with two well-known methods from the literature. The results indicate that the first two suggested methods perform well especially when the number of states in the augmented system is less than 10 and 20, respectively. The third method has comparable performance with two methods from literature when the number of states in the augmented system is less than 25.

Les travaux présentés dans cette thèse ont été effectués au Centre de Recherche en Automatique de Nancy (CRAN). Ils portent sur l'observation et la commande des systèmes singuliers non linéaires. Dans un premier temps nous nous sommes intéressés à la synthèse d'observateur et au filtrage H infini des systèmes singuliers bilinéaires. Dans un deuxième temps, nous avons étudié la synthèse d'observateur pour les systèmes singuliers non linéaires Lipschitziens. La dernière partie de ce travail concerne la stabilisation et la commande basée observateurs des systèmes singuliers non linéaires. L'objectif de ce travail a été de proposer des résultats facilement implémentables et de couvrir une large classe de systèmes non linéaires. La contribution principale de ce mémoire a été de proposer des observateurs H infini pour les systèmes singuliers non linéaires, en utilisant le non biais de l'erreur d'estimation. Les paramètres de ces observateurs sont obtenus par la résolution des inégalités matricielles linéaires (LMIs). Le deuxième apport concerne la synthèse de commande stabilisante et l'utilisation d'un des observateurs proposés dans cette thèse pour la synthèse d'une commande basée observateur pour les systèmes singuliers non linéaires. Cette dernière est réalisée grâce à la réécriture des fonctions non linéaires sous des formes adéquates à l'application de la commande des systèmes / This thesis work is realized in the Research Center in Automatic Control of Nancy (CRAN). It concerns the observation and control of nonlinear singular systems. Firstly, we were interested in the observer design and H infinity filtering for singular bilinear systems. In a second step, we studied the observers design for Lipschitz nonlinear singular systems. The last part of this work relates to the stabilization and observer based controller for a classe of singular nonlinear systems. The objective is to develop a simple and straightforward results which covers a large class of nonlinear systems. The main contribution of this thesis is in the H infinity observers design for nonlinear singular systems. It is based on the parametrization of the solution of the constrained generalized Sylvester equation. The second contribution relates to the design of stabilizing control and using the proposed observer to design an obsever based controller for nonlinear singular systems. Solutions of these problems are obtained by using Linear Matrix Inequalities (LMI) Formulation

The thesis consists of an introduction and four appended papers. In the introduction we give an overview of pulse-modulated systems and provide a few examples of such systems. Furthermore, we introduce the so-called dynamic phasor model which is used as a basis for analysis in two of the appended papers. We also introduce the harmonic transfer function and finally we provide a summary of the appended papers. The first paper considers stability analysis of a class of pulse-width modulated systems based on a discrete time model. The systems considered typically have periodic solutions. Stability of a periodic solution is equivalent to stability of a fixed point of a discrete time model of the system dynamics. Conditions for global and local exponential stability of the discrete time model are derived using quadratic and piecewise quadratic Lyapunov functions. A griding procedure is used to develop a systematic method to search for the Lyapunov functions. The second paper considers the dynamic phasor model as a tool for stability analysis of a general class of pulse-modulated systems. The analysis covers both linear time periodic systems and systems where the pulse modulation is controlled by feedback. The dynamic phasor model provides an $\textbf{L}_2$-equivalent description of the system dynamics in terms of an infinite dimensional dynamic system. The infinite dimensional phasor system is approximated via a skew truncation. The truncated system is used to derive a systematic method to compute time periodic quadratic Lyapunov functions. The third paper considers the dynamic phasor model as a tool for harmonic analysis of a class of pulse-width modulated systems. The analysis covers both linear time periodic systems and non-periodic systems where the switching is controlled by feedback. As in the second paper of the thesis, we represent the switching system using the L_2-equivalent infinite dimensional system provided by the phasor model. It is shown that there is a connection between the dynamic phasor model and the harmonic transfer function of a linear time periodic system and this connection is used to extend the notion of harmonic transfer function to describe periodic solutions of non-periodic systems. The infinite dimensional phasor system is approximated via a square truncation. We assume that the response of the truncated system to a periodic disturbance is also periodic and we consider the corresponding harmonic balance equations. An approximate solution of these equations is stated in terms of a harmonic transfer function which is analogous to the harmonic transfer function of a linear time periodic system. The aforementioned assumption is proved to hold for small disturbances by proving the existence of a solution to a fixed point equation. The proof implies that for small disturbances, the approximation is good. Finally, the fourth paper considers control synthesis for switched mode DC-DC converters. The synthesis is based on a sampled data model of the system dynamics. The sampled data model gives an exact description of the converter state at the switching instances, but also includes a lifted signal which represents the inter-sampling behavior. Within the sampled data framework we consider H-infinity control design to achieve robustness to disturbances and load variations. The suggested controller is applied to two benchmark examples; a step-down and a step-up converter. Performance is verified in both simulations and in experiments. / QC 20100628