The goal of this diploma work is to design a control for permanent magnet synchronous motor in sliding mode. The introduction describes a synchronous motor, sensors which are used in the control process as well as power devices. Further, there is description of mathematical model for the synchronous motor. Another part of the diploma work deals with classic vector control for this kind of motor followed by the sliding mode control for the motor. At the end, there is presented an algorithm which has been implemented in the processor designed for this equipment. All the controllers used in the equipment have been tested on motor simulations. In conclusion, there is a target analysis and facts finding.

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.

L’utilisation des AUV pour une exploitation durable des ressources océaniques est pertinente. Un robot sous-marin peut être utilisé comme plateforme pour observer, recueillir des informations sur l’environnement marin. Afin d’améliorer la qualité des observations et d’augmenter la capacité de navigation, de nombreuses questions doivent être abordées et examinées simultanément. Nous abordons ici le problème du pilotage de ces robots autonomes.Atteindre la maniabilité nécessaire dépend de deux facteurs clés: un modèle hydrodynamique précis et un système de contrôle performant. Cependant, le coût de développement d’un modèle précis est généralement très élevé. De plus, lorsque la géométrie du robot est complexe, il devient très difficile d’identifier de manière pertinente les paramètres dynamiques et hydrodynamiques. En outre, du point de vue de la commande, les modèles obtenus sont non linéaire, en particuliers pour les amortissements.De nombreux phénomènes dynamiques ne sont pas modélisés: dynamiques internes au robot, environnementales, liées aux bruits des capteurs, aux retards intrinsèques. Dans les concours de robotique sous-marine, il est confirmé que le traditionnel régulateur Proportionnel-Intégral-Dérivé (PID) est peu efficace pour les robots légers. Dans ce cas, notre champ d’application est plus axé sur la combinaison des approches de modélisation numérique et la commande robuste.Dans ce travail, nous proposons un schéma de régulation basé sur la commande robuste et la modélisation. La régulation robuste a été mise en place et validée en mer sur un AUV de la marque CISCREA et la solution proposée utilise Computational Fluid Dynamic (CFD) pour caractériser les deux paramètres hydrodynamiques (matrice de masse ajoutée et matrice d’amortissement). Puis un modèle à quatre degrés de liberté est construit pour le CISCREA. Les résultats numériques et expérimentaux sont alors comparés.La commande robuste proposée est basée sur une compensation non linéaire et de la commande H∞. La validation de la robustesse a été testée par simulation en Matlab et finalement validée par des essais en mer à Brest. La simulation et l’expérience montrent que l’approche en plus d’être robuste est plus rapide que les régulateurs précédemment proposés. / Autonomous Underwater Vehicle (AUV) is a relevant technology for the sustainable use of ocean resources. AUV can be used as an important ocean observing platform to collect information on marine environmental characteristics for research and industry fields. In order to improve the observation quality and increase the navigation ability, many issues should be addressed and considered simultaneously. Achieve necessary maneuverability depends on two key factors: an accurate hydrodynamic model and an advanced control system. However, the cost to develop an accurate hydrodynamic model, which shrinks the uncertainty intervals, is usually high. Meanwhile, when the robot geometry is complex, it becomes very difficult to identify its dynamic and hydrodynamic parameters. In addition, according to the quadratic damping factor, underwater vehicle dynamic and hydrodynamic model is nonlinear from the control point of view. Moreover, unmodeled dynamics, parameter variations and environmental disturbances create significant uncertainties among the nominal model and the reality. Sensor noise, signal delay as well as unmeasured states also affect the stability and control performance of the motion control system. In many of our underwater competitions, it has been confirmed that the traditional Proportional-Integral-Derivative (PID) regulation is less efficient for low mass AUV. In this case, our scope is more focused on the combination of numerical modeling approaches and robust control schemes. In this work, we proposed a model based robust motion control scheme. Without loss of generality, a robust heading controller was implemented and validated in the sea on cubic-shaped CISCREA AUV. The proposed solution uses cost efficient Computational Fluid Dynamic (CFD) software to predict the two hydrodynamic key parameters: The added mass matrix and the damping matrix. Four Degree of Freedom (DOF) model is built for CISCREA from CFD calculation. Numerical and experimental results are compared. Besides, the proposed control solution inherited the numerically obtained model from previous CFD calculation. Numerically predicted the actuator force compensates the nonlinear damping behavior result in a linear model with uncertainties. Based on the bounded linear nominal model, we proposed H∞ approach to handle the uncertainties, we used kalman filter to estimate unmeasured states such as angular velocity and we developed smith compensator to compensate the sensor signal delay. The proposed robust heading control application uses only one compass as feedback sensor. This is important while AUV is working at certain depth where only magnetic sensors still work. Our robust control scheme was simulated in Matlab and validated in the sea near Brest. Simulation shows obvious advantage of the proposed robust control approach. Meanwhile, the proposed robust heading control is much faster than PID controller. The robust controller is insensitive to uncertainties and has no overshot. From both simulations and real sea experiments, we found our proposed robust control approach and the one compass heading control applications are efficient for low mass and complex-shaped AUV CISCREA.

Récemment, le robot dirigeable a attiré l'attention de plus en plus des chercheurs grâce à ses avantages par rapport à d'autres aéronefs, tels que la capacité de VTOL, le vol stationnaire et à basse vitesse, une grande autonomie, et une interaction Homme-Robot sûre, etc. Ainsi c'est une plate-forme idéale pour diverses applications d'intérieur. Dans cette thèse, nous étudions la modélisation et le contrôle du mouvement d'un robot dirigeable d'intérieur et développons un prototype pour les opérations intérieures comme la surveillance. Le travail est composé de parties théoriques et pratiques. Concernant la partie théorique, d’abord, sous des hypothèses raisonnables, le modèle dynamique à 6-DOF est simplifié et divisé en deux parties indépendantes: le mouvement de l’altitude et le mouvement dans le plan horizontal. Ensuite, à fin d'assurer la précision de la modélisation et du contrôle, le modèle nominal est complété par des termes de perturbation qui sont estimés en temps réel et compensés dans les contrôleurs conçus. Des simulations sont effectuées pour vérifier les performances et la robustesse des contrôleurs. Pour la partie pratique du travail, basée sur l'analyse des fonctionnalités du robot afin de réaliser les applications intérieures souhaitées, le matériel du robot dirigeable est conçu et créé. Enfin, de vrais tests sont effectués sur la plate-forme de robot dirigeable pour la validation des lois de contrôle de mouvement conçues, et des résultats satisfaisants sont obtenus. / Recently, the blimp robot has attracted more and more attentions of the researchers for its advantages compared to other aircrafts, such as ability for VTOL, stationary and low speed flight, long endurance in air and safe Human-Robot interaction, etc. Therefore it is an ideal platform for various indoor applications. In this thesis, we study the modeling and motion control of an indoor blimp robot, and develop a real robot for indoor operations such as the long-term surveillance. The work is composed of both theoretical and practical parts. For the theoretical part, first, under reasonable assumptions, the 6-DOF dynamic model is simplified and divided into two independent parts: the altitude motion and the horizontal plane movement. Then, to ensure the accuracy of modeling and control, the nominal model is complemented with disturbance terms which are estimated in real-time and compensated in the designed controllers. Simulations are carried out to verify the performance and robustness of the controllers. For the practical part of the work, based on the functionality analysis of the robot to achieve desired indoor applications, the hardware of the blimp robot is conceived and created. Finally, real tests are made on the blimp robot platform for the validation of the designed motion control laws, and satisfying results are obtained.

The work in this dissertation concerns the construction of a robust iterative learning control (ILC) algorithm for a class of systems characterized by measurement delays, parametric uncertainty, and linear parameter varying (LPV) dynamics. One example of such a system is the twin roll strip casting process, which provides a practical motivation for this research. I propose three ILC algorithms in this dissertation that advance the state of the art. The first algorithm compensates for measurement delays that are longer than a single iteration of a periodic process. I divide the delay into an iterative and residual component and show how each component effects the asymptotic stability properties of the ILC algorithm. The second algorithm is a coupled delay estimation and ILC algorithm that compensates for time-varying measurement delays. I use an adaptive delay estimation algorithm to force the delay estimate to converge to the true delay and provide stability conditions for the coupled delay estimation and ILC algorithm. The final algorithm is a norm optimal ILC algorithm that compensates for LPV dynamics as well as parametric uncertainty and time delay estimation error. I provide a tuning method for the cost function weight matrices based on a sufficient condition for robust convergence and an upper bound on the norm of the error signal. The functionality of all three algorithms is demonstrated through simulated case studies based on an identified system model of the the twin roll strip casting process. The simulation testing is also augmented with experimental testing of select algorithms through collaboration with an industrial sponsor.

In this dissertation the problem of recognising vehicle licence plates of which the sym¬bols can not be segmented by standard image processing techniques is addressed. Most licence plate recognition systems proposed in the literature do not compensate for dis¬torted, obscured and damaged licence plates. We implemented a novel system which uses a neural network/ hidden Markov model hybrid for licence plate recognition. We implemented a region growing algorithm, which was shown to work well when used to extract the licence plate from a vehicle image. Our vertical edges algorithm was not as successful. We also used the region growing algorithm to separate the symbols in the licence plate. Where the region growing algorithm failed, possible symbol borders were identified by calculating local minima of a vertical projection of the region. A multilayer perceptron neural network was used to estimate symbol probabilities of all the possible symbols in the region. The licence plate symbols were the inputs of the neural network, and were scaled to a constant size. We found that 7 x 12 gave the best character recognition rate. Out of 2117 licence plate symbols we achieved a symbol recognition rate of 99.53%. By using the vertical projection of a licence plate image, we were able to separate the licence plate symbols out of images for which the region growing algorithm failed. Legal licence plate sequences were used to construct a hidden Markov model contain¬ing all allowed symbol orderings. By adapting the Viterbi algorithm with sequencing constraints, the most likely licence plate symbol sequences were calculated, along with a confidence measure. The confidence measure enabled us to use more than one licence plate and symbol segmentation technique. Our recognition rate increased dramatically when we com¬bined the different techniques. The results obtained showed that the system developed worked well, and achieved a licence plate recognition rate of 93.7%. / Dissertation (MEng (Computer Engineering))--University of Pretoria, 2002. / Electrical, Electronic and Computer Engineering / unrestricted

The growing need for ocean surveillance and exploration has pushed the development of novel autonomous underwater vehicle (AUV) technology. A current trend is to make use of bio-inspired propulsor to increase the overall system efficiency and performance, an improvement that has deep implications in the dynamics of the system. The goal of this dissertation is to propose a generic robust control framework specific for bio-inspired autonomous underwater vehicles (BIAUV). These vehicles utilize periodic oscillation of a flexible structural component to generate thrust, a propulsion mechanism that can be tuned to operate under resonance and consequently improve the overall system efficiency. The control parameter should then be selected to keep the system operating in such a condition. Another important aspect is to have a controller design technique that can address the time-varying behaviors, structured uncertainties and system nonlinearities. To address these needs a robust, model-based, nonlinear controller design technique is presented, called digital sliding mode controller (DSMC), which also takes into account the discrete implementation of these laws using microcontrollers. The control law is implemented in the control of a jellyfish-inspired autonomous underwater vehicle. / Ph. D.

No description available.

In modern manufacturing industries, many applications require precision motion control of multi-agent systems, like multi-joint robot arms and multi-axis machine tools. Cutter (end effector) should stay as close as possible to the reference trajectory to ensure the quality of the final products. In conventional computer numerical control (CNC), the control unit of each axis is independently designed to achieve the best individual tracking performance. However, this becomes less effective when dealing with multi-axis contour following tasks because of the lack of coordination among axes. This dissertation studies the control of multi-axis machine tools with focus on reducing the contour error. The proposed research explicitly addresses the minimization of contour error and treats the multi-axis machine tool as a multi-input-multi-output (MIMO) system instead of several decoupled single-input-single-output (SISO) systems. New control schemes are developed to achieve superior contour following performance even in the presence of disturbances. This study also extends the applications of the proposed control system from plane contours to regular contours in R3. The effectiveness of the developed control systems is experimentally verified on a micro milling machine.

This master thesis studies the implementation of a Robust MPC controllerin marine vessels on different tasks. A tube based MPC is designed based onsystem linearization around the target point guaranteeing local input to statestability of the respective linearized version of the original nonlinear system.The method is then applied to three different tasks: Dynamic positioningon which recursive feasibility of the nominal MPC is also guaranteed, Speed-Heading control and trajectory tracking with the Line of sight algorithm.Numerical simulation is then provided to show technique’s effectiveness. / Detta examensarbete studerar design och implementering av en robustmodellprediktiv regulator (MPC) för marina fartyg. En tub-baserad MPCär designad baserad på linjärisering av systemdynamiken runt en målpunkt,vilket garanterar local insignal-till-tillstånds stabilitet av det linjäriserade systemet.Metoden är sedan applicerad på tre olika uppgifter: dynamisk positionering,för vilken vi även kan garantera rekursiv lösbarhet för den nominellaregulatorn; riktningsstyrning; och banfötljning med en siktlinje-algoritm. Numeriskasimuleringsstudier bekräftar metodens effektivitet.