No description available.

No description available.

No description available.

In this thesis we present theoretical and numerical results for a feedback control problem defined by a thermal fluid. The problem is motivated by recent interest in designing and controlling energy efficient building systems. In particular, we show that it is possible to locally exponentially stabilize the nonlinear Boussinesq Equations by applying Neumann/Robin type boundary control on a bounded and connected domain. The feedback controller is obtained by solving a Linear Quadratic Regulator problem for the linearized Boussinesq equations. Applying classical results for semilinear equations where the linear term generates an analytic semigroup, we establish that this Riccati-based optimal boundary feedback control provides a local stabilizing controller for the full nonlinear Boussinesq equations. In addition, we present a finite element Galerkin approximation. Finally, we provide numerical results based on standard Taylor-Hood elements to illustrate the theory. / Ph. D.

Unmanned aerial systems have been widely used for variety of civilian applications over the past few years. Some of these applications require accurate guidance and control. Consequently, Unmanned Aerial Vehicle (UAV) guidance and control attracted many researchers in both control theory and aerospace engineering. Flying wings, as a particular type of UAV, are considered to have one of the most efficient aerodynamic structures. It is however difficult to design robust controller for such systems. This is due to the fact that flying wings are highly sensitive to control inputs. The focus of this thesis is on modeling and control design for a UAV system. The platform understudy is a flying wing developed by SmartPlanes Co. located in Skellefteå, Sweden. This UAV is particularly used for topological mapping and aerial photography. The novel approach suggested in this thesis is to use two controllers in sequence. More precisely, Linear Quadratic Regulator (LQR) is suggested to provide robust stability, and Proportional, Integral, Derivative (PID) controller is suggested to provide reference signal regulation. The idea behind this approach is that with LQR in the loop, the system becomes more stable and less sensitive to control signals. Thus, PID controller has an easier task to do, and is only used to provide the required transient response. The closed-loop system containing the developed controller and a UAV non-linear dynamic model was simulated in Simulink. Simulated controller was then tested for stability and robustness with respect to some parametric uncertainty. Obtained results revealed that the LQR successfully managed to provide robust stability, and PID provided reference signal regulation.

In this thesis, an optimal multivariable current control method is presented for the highspeed permanent magnet synchronous motor (HS-PMSM). The HS-PMSMs have growing applications in the industry. One of their major challenges is the low switching to fundamental frequency ratio (SFR). At high speed and low SFR, the control time delays including the digital, the PWM, and sensor delays become more pronounced and lead to oscillations and even instabilities. A well-known method for delay compensation is to advance the phase angle of control input for a known amount. In practice, the exact delay is unknown, and mismatch in the compensating angle causes deteriorating effect on the system. In the proposed method, the digital and PWM delays are modelled and integrated with an optimal multivariable controller. This method improves the stability margin and achievable speed margin compared to the traditional phase advancing delay compensation (PADC) method. Combining the proposed delay modeling and the PADC method further improves the response, as the uncertain sensor delays can be compensated greatly. Besides the delay, the cross-coupling between ���� axis affects the dynamic performance of the machine. The proposed multivariable approach considers and directly addresses the coupling. Dynamic performance of the PMSM with the proposed method is thoroughly compared with the conventional delay compensation method. The proposed method is validated through extensive simulation studies on a 2 kW high-speed machine.

This thesis project aims to model a quadcopter and design a linear quadratic regulator (LQR) by means of Matlab/Simulink. To this purpose, the LQR-based optimal control theory for controllinga quadcopter is first studied which includes state-space representation (SSR) of a dynamicprocess or system, cost function, LQR, quadcopter flight dynamics and system linearization. A quadcopter model is developed in Matlab/Simulink, followed by the implementation of a LQR-based control system. The LQR parameters are tuned and the system is tested under various flight conditions (wind disturbance, in the simulation, specific/simplified model, etc.). The simulation results show that the LQR is an effective controller for maintaining stable hover at a height straight up and compensating for wind disturbances. However, when the quadcopter moves to a new position, oscillations occur, highlighting the limitations of the LQR due to its reliance on a simplified and linearized model. Additionally, modifications to the model parameters, such as mass and inertia, impact the system performance, indicating potential robustness issues with the controller. It can be concluded that Matlab/Simulink is an effective tool for quadcopter modeling, LQR designing and LQR performance analyzing. In this thesis project, only the LQR method is used for controlling a quadcopter and the LQR tuning process is not efficient. In future work other techniques such as regional linearization and alternative non-linear controllers, like model predictive control (MPC) or sliding mode control (SMC), can be explored. Development of optimization algorithms for LQR tuning in the LQR method is highly recommended.

Ziel der Arbeit ist die anschauliche Demonstration der Leistungsfähigkeit von Hardware- Systemen zur Regelung instabiler Systeme am Beispiel des Inversen Pendels. Dabei handelt es sich um das Balancieren eines Stabes, einem Standard-Problem der Regelungstechnik. Es wird die Konzeption und Implementierung einer Hardware-Regelung in einem FPGA-Prototypenboard zur Realisierung dieser Aufgabe beschrieben. Die Regelung basiert mit LQR-Entwurf und Kalman-Filter auf klassischen Methoden der Regelungstechnik. Zur Demonstration der Regelung wurde ein mechanischer Aufbau vorgenommen, an dem die Funktionsfähigkeit des Inversen Pendels praktisch gezeigt wurde.

De nos jours, les applications utilisant des quadrirotors autonomes sont en plein essor. La surveillance et la sécurité de sites industriels ou sensibles, de zones géographiques pour l’agriculture par exemple sont quelques-unes des applications les plus célèbres des véhicules aériens sans pilote (UAV). Actuellement, certains chercheurs et scientifiques se concentrent sur le déploiement multi-drones pour l’inspection et la surveillance de vastes zones. L’objectif de cette thèse est de concevoir des algorithmes afin de réaliser une commande de vol en formation distribuée/décentralisée de multi-UAVs en temps réel dans une perspective de systèmes de systèmes. Tout d’abord, nous avons passé en revue certains travaux récents de la littérature sur la commande de vol en formation et la commande de quadrirotors. Nous avons présenté une brève introduction sur les systèmes de systèmes, leur définition et leurs caractéristiques. Ensuite, nous avons introduit la commande de vol en formation avec ses structures les plus utilisées dans la littérature. Nous avons alors présenté quelques travaux existants traitant du flocking (comportement de regroupement en flotte), les méthodes de modélisation les plus utilisés pour les quadrirotors et quelques approches de commande les plus utilisées pour stabiliser des quadrirotors. Deuxièmement, nous avons utilisé la structure de la commande comportementale pour réaliser un vol en formation de plusieurs UAVs. Nous avons conçu un comportement pour réaliser le vol en formation de multi-UAVs sans fragmentation. Le comportement proposé traite le problème flocking dans une perspective globale, c’est-à-dire, nous avons inclus une tendance dans chaque drone pour former une formation. Les défis des Systèmes de systèmes nous a motivés à chercher des algorithmes de flocking et de consensus introduits dans la littérature qui peuvent être utiles pour répondre à ces défis. Cela nous a amenés à proposer quatre lois de commande en visant à être compatibles avec le modèle non linéaire des quadrirotors et pouvant être expérimentés sur des plates-formes réelles. Les lois de commande ont été exécutées à bord de chaque quadrirotor dans la formation et chaque quadrirotor interagit avec ses voisins pour assurer un vol en formation sans collision. Enfin, nous avons validé nos lois de commande par des simulations et des expériences en temps réel. Pour la simulation, nous avons utilisé un simulateur de multi quadrirotors développé au laboratoire Heudiasyc. Pour les expériences, nous avons mis en œuvre nos lois de contrôle sur des quadrirotors ArDrone2 évolués dans un environnement intérieur équipé d’un système de capture de mouvement (Optitrack). / Nowadays, applications of autonomous quadrotors are increasing rapidly. Surveillance and security of industrial sites, geographical zones for agriculture for example are some popular applications of Unmanned Aerial Vehicles (UAVs). Nowadays, researchers and scientists focus on the deployment of multi-UAVs for the inspection and the surveillance of large areas. The objective of this thesis is to design algorithms and techniques to perform a real-time distributed/decentralized multi-UAVs flight formation control, from a system of systems perspective. Firstly, we reviewed recent works of the literature about flight formation control and the control of quadrotors. We presented a brief introduction about systems of systems, their definition and characteristics. Then, we introduced the flight formation control with its most used structures in the literature, some existing works dealing with flocking. Finally, we presented the most used modeling methodologies for quadrotors and some control approaches that are used to stabilize quadrotors. Secondly, we used the behavioral-based control structure to achieve a multiple UAV flocking. We conceived a behavior intending to address the control design towards a successful achievement of the flocking task without fragmentation. The proposed behavior treats the flocking problem from a global perspective, that is, we included a tendency of separated UAVs to form a flock.System of systems challenges motivated us to look for flocking and consensus algorithms introduced in the literature that could be helpful to answer to these challenges. This led us to propose four flocking control laws aiming at being compatible with the nonlinear model of quadrotors and at being implemented on experimental platforms. The control laws were run aboard each quadrotor in the flock. By running the control law, each quadrotor interacts with its neighbors to ensure a collision-free flocking. Finally, we validated our proposed control laws by simulations and real-time experiments. For the simulation, we used a PC-based simulator of flock of multiple quadrotors which was developed at Heudiasyc laboratory. For experiments, we implemented our control laws on ArDrone2 quadrotors evolved in an indoor environment equipped with an Optitrack motion capture system.

Made available in DSpace on 2016-08-17T14:52:52Z (GMT). No. of bitstreams: 1 Carlos Cesar Teixeira Ferreira.pdf: 819618 bytes, checksum: d77aa555d25af8f110fac9381a4b6c4d (MD5) Previous issue date: 2004-03-25 / This work presents a proposal for Eigenstructure Assignment in dynamic stochastic multivariable systems, using LQG/LTR Robust Controllers and Evolutionary Computation. It shows the importance and influence of the Eigenstructure Assignment on the systems dynamic response. It solves the Eigenstructure Assignment problem of the control problem through Linear Quadratic Regulator Design and Genetic Algorithm, developed to perform the search of the state and control weighting matrices in order to assign the Eigenstructure. The Eigenstructure Assignment problem of stochastic state estimation is formulated and solved by using Kalman Filter Design and Genetic Algorithm, now developed to search the state disturbance and measurement noise covariances matrices in order to find an adequate estimator. The Eigenstructure Assignment problem for the stochastic multivariable control with observer is formulated as LQG/LTR Robust Control problem with Loop Transfer Recovery at the Input. This proposal for Eigenstructure Assignment using LQG/LTR Controllers is examined on dynamical system model that representing an aircraft. / Apresenta-se neste trabalho um método para Alocação de Auto-estrutura em sistemas dinâmicos estocásticos multivariáveis, utilizando-se o Projeto de Controladores Robustos LQG/LTR e Computação Evolutiva. Mostra-se a importância e influência da Alocação de Auto-estrutura na resposta de sistemas dinâmicos. Resolve-se o problema da Alocação de Auto-estrutura do problema de controle através do Projeto do Regulador Linear Quadrático e Algoritmo Genético, desenvolvido para realizar a busca das matrizes de ponderação do estado e do controle de forma a alocar a Auto-estrutura. Formula-se e resolve-se o problema de Alocação de Auto-estrutura do estimador de estado estocástico, utilizando-se Filtro de Kalman e Algoritmo Genético, agora desenvolvido para buscar as matrizes de covariâncias da perturbação no estado e do ruído de medida, de forma a encontrar um estimador adequado. Propõe-se e implementa-se a solução do problema de Alocação de Auto-estrutura para o projeto de controle multivariável com observador estocástico, formulado como um problema de Controle Robusto LQG/LTR com Recuperação da Malha de Transferência na Entrada. Verifica-se esta proposta de Alocação de Auto-estrutura via Controladores LQG/LTR em um modelo de um sistema dinâmico que representa uma aeronave.