This research work provides the development of an Adaptive Flight Control System (AFCS) for autonomous hover of a Rotary-wing Unmanned Aerial Vehicle (RUAV). Due to the complex, nonlinear and time-varying dynamics of the RUAV, indirect adaptive control using the Model Predictive Control (MPC) is utilised. The performance of the MPC mainly depends on the model of the RUAV used for predicting the future behaviour. Due to the complexities associated with the RUAV dynamics, a neural network based black box identification technique is used for modelling the behaviour of the RUAV. Auto-regressive neural network architecture is developed for offline and online modelling purposes. A hybrid modelling technique that exploits the advantages of both the offline and the online models is proposed. In the hybrid modelling technique, the predictions from the offline trained model are corrected by using the error predictions from the online model at every sample time. To reduce the computational time for training the neural networks, a principal component analysis based algorithm that reduces the dimension of the input training data is also proposed. This approach is shown to reduce the computational time significantly. These identification techniques are validated in numerical simulations before flight testing in the Eagle and RMAX helicopter platforms. Using the successfully validated models of the RUAVs, Neural Network based Model Predictive Controller (NN-MPC) is developed taking into account the non-linearity of the RUAVs and constraints into consideration. The parameters of the MPC are chosen to satisfy the performance requirements imposed on the flight controller. The optimisation problem is solved numerically using nonlinear optimisation techniques. The performance of the controller is extensively validated using numerical simulation models before flight testing. The effects of actuator and sensor delays and noises along with the wind gusts are taken into account during these numerical simulations. In addition, the robustness of the controller is validated numerically for possible parameter variations. The numerical simulation results are compared with a base-line PID controller. Finally, the NN-MPCs are flight tested for height control and autonomous hover. For these, SISO as well as multiple SISO controllers are used. The flight tests are conducted in varying weather conditions to validate the utility of the control technique. The NN-MPC in conjunction with the proposed hybrid modelling technique is shown to handle additional disturbances successfully. Extensive flight test results provide justification for the use of the NN-MPC technique as a reliable technique for control of non-linear complex dynamic systems such as RUAVs.

[Truncated abstract] The use of uncertainty analysis is gaining considerable attention in catchment hydrological modeling. In particular, the choice of an appropriate model structure, the identifiability of parameter values, and the reduction of model predictive uncertainty are deemed as essential elements of hydrological modelling. The chosen model structure must be parsimonious, and the parameters used must either be derivable from field measured data or inferred unambiguously from analysis of catchment response data. In this thesis, a long-term water balance model for the Susannah Brook catchment in Western Australia has been pursued using the ?downward approach?, which is a systematic approach to determine the model with the minimum level of complexity, with parameter values that in theory are derivable from existing physiographic data relating to the catchment. Through the analysis of the rainfall-runoff response at different timescales, and the exploration of the climate, soil and vegetation controls on the water balance response, an initial model structure was formulated, and a priori model parameter values estimated. Further investigation with the use of auxiliary data such as deuterium concentration in the stream and groundwater level data exposed inadequacies in the model structure. Two more model structures were then proposed and investigated through formulating alternative hypotheses regarding the underlying causes of observed variability, including those associated with the absence of a contribution of deep groundwater flow to the streamflow, which was indicated by deuterium concentration and internal dynamics characterized by the observed groundwater levels. ... These differences are due to differences in the time delay between rainfall and recharge between upland and riparian regions. The ages of water recharging the groundwater and discharging from the catchment were estimated by assuming a piston flow mechanism. In the deeper, upland soils, the age of recharging water was considerably larger than the unsaturated zone delay would suggest; a recharge response 16 days after an infiltration event may involve water as much as 160 days old. On the other hand, the delay and the age of recharging water were much lower in the shallow riparian zone. Where the upland zone contributes significantly to discharge, the predicted difference between the rainfall-discharge response time and the average age of discharging water can be significant.

This thesis addresses the problems of design and control of small cooperative unmanned autonomous quadrotor aerial vehicles. A new approach is proposed, for the modeling of the system’s dynamics using linearized Piecewise AffineModels. The Piecewise Affine dynamic–models cover a large part of the quadrotor’s flight envelope while also taking into account the additive effects of environmental disturbances. The effects of aerodynamic forces and moments were also examined. A small quadrotor is designed and developed that emphasizes in the areas of increased on–board computational capabilities, state estimation and modular connectivity. Based on the translational and rotational system’s dynamics: a) a switching model predictive controller, b) an explicitly solved constrained finite time optimal control strategy, and c) a cascade control scheme comprised of classical Proportional Integral Derivative control scheme augmented with angular acceleration feedback, were designed and experimentally tested in order to achieve trajectory tracking under the presence of wind–gusts. The efficiency of the proposed control methods was verified through extended experimental studies. The final quadrotor design utilizes a powerful control unit, a sensor system that provides state estimation based on inertial sensors, ultrasound sonars, GPS and vision chips, and an efficient actuating system. The research effort extended in the field of unmanned aerial vehicles cooperation. Cooperation strategies were proposed in order to address the problems of: a) Forest Fire Monitoring and b) Unknown Area Exploration and Target Acquisition. The Forest FireMonitoring algorithm is formulated based on consensus systems theory formulated as a spatiotemporal rendezvous problem in between the quadrotors. The Area Exploration and Target Acquisition algorithm is formulated based on market–based approaches. / Η συγκεκριμένη διατριβή καταπιάνεται με τα προβλήματα της σχεδίασης και ελέγχου μικρού μεγέθους συνεργαζόμενων μη επανδρωμένων αεροσκαφών με έμφαση στα συστήματα Κάθετης Απογείωσης και Προσγείωσης και ιδιαίτερα στη συστήματα τύπου Quadrotor. Μια νέα προσέγγιση για την μοντελοποίηση της δυναμικής του συστήματος η οποία βασίζεται στη θεωρία των Piecewise Affine συστημάτων προτείνεται. Η μοντελοποίηση με βάση τη θεωρία των Piecewise Affine συστημάτων καλύπτει ένα μεγάλο μέρος του φακέλου πτήσης του αεροσκάφους καθότι συνυπολογίζει μέρος της μη-γραμμικότητας του συστήματος ενώ παράλληλα δίνει τη δυνατότητα να χρησιμοποιηθούν τα ιδιαίτερα ανεπτυγμένα εργαλεία του γραμμικού ελέγχου. Αναπτύσσεται νέα πειραματική πλατφόρμα αεροσκάφους τύπου quadrotor η οποία χαρακτηρίζεται από ιδιαίτερες ικανότητες υπολογιστικής ισχύος, αυτόνομη εκτίμηση κατάστασης, πολλαπλή συνδεσιμότητα και αποδοτικό σύστημα πρόωσης. Η τελική πλατφόρμα quadrotor ελικοπτέρου UPATcopter ενσωματώνει μικρουπολογιστικό σύστημα υψηλών δυνατοτήτων, ειδικά συστήματα εκτίμησης κατάστασης τόσο σε εσωτερικούς όσο και σε εξωτερικούς χώρους μέρος των οποίων αναπτύχθηκε στα πλαίσια της διατριβής και αποδοτικό υποσύστημα πρόωσης. Τρεις διαφορετικοί νόμοι ελέγχου αναπτύχθηκαν και δοκιμάστηκαν πειραματικά. Αρχικά δοκιμάσθηκε ένας Constrained Finite Time Optimal Controller, ο οποίος υπολογίζεται πολύ-παραμετρικά και συνυπολογίζει την επίδραση των περιορισμών εισόδου και κατάστασης. Ο συγκεκριμένος ελεγκτής υπολογίσθηκε με βάση μια οικογένεια Piecewise Affine αναπαραστάσεων του υποσυστήματος προσανατολισμού και δοκιμάσθηκε επιτυγχάνοντας αποδοτικό έλεγχο του προσανατολισμού του σκάφους. Ακολούθως δοκιμάσθηκε ένας Switching Model Predictive Control βασισμένος στην Piecewise Affine μοντελοποίηση του συστήματος ο οποίος επίσης συνυπολογίζει την επίδραση των περιορισμών του συστήματος και του ρόλου των διαταραχών. Με τη χρήση αυτού του ελεγκτή επιτεύχθηκε έλεγχος προσανατολισμού και θέσης του αεροσκάφους τόσο σε άπνοια όσο και υπό την επίδραση ισχυρών διαταραχών ανέμου. Επιπρόσθετα, δοκιμάσθηκε ελεγκτής βασισμένος στη θεωρία PID ελέγχου επαυξημένος με ανάδραση γωνιακής επιτάχυνσης του συστήματος. Τέλος, η έρευνα επεκτάθηκε και στις στρατηγικές συνεργασίας μη επανδρωμένων αεροσκαφών προτείνοντας δύο αλγόριθμους. Συγκεκριμένα προτάθηκε αλγόριθμος για την αντιμετώπιση των προβλημάτων επιθεώρησης δασικής πυρκαγιάς και αλγόριθμος εξερεύνησης μιας άγνωστης περιοχής από ομάδα ετερογενών αεροσκαφών.

Thesis (MEng)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: The development of fast and efficient processors, programmable devices and high power semiconductors has led to the increased use of semiconductors directly in the power supply path in order to achieve strict power quality standards. New and advanced algorithms are used in the process and calculated on-line to bring about the required fast response to voltage variations. Losses in high voltage semiconductors increase with increased operating frequencies. A balance between semiconductor power losses and power quality is achieved through control of power semiconductor switching frequencies. A predictive control algorithm to achieve high power quality and limit the power losses in the high power semiconductor switches through switching frequency control is discussed for a tap switched voltage regulator. The quality of power, voltage regulator topology and the control algorithm are discussed. Simulation results of output voltage and current are shown when the control algorithm is used to control the regulator. These results are verified by practical measurements on a synchronous buck converter. / AFRIKAANSE OPSOMMING: Die ontwikkeling van vinnige en doeltreffende verwerkers, programmeerbare toestelle en hoëdrywings halfgeleiers het gelei tot 'n groter gebruik van halfgeleiers direk in die kragtoevoer pad om streng elektriese toevoer kwaliteit standaarde te bereik. Nuwe en gevorderde algoritmes word gebruik in die proses en word aan-lyn bereken om die nodige vinnige reaksie tot spanningswisselinge te gee. Verliese in hoë-spannings halfgeleiers verhoog met hoër skakel frekwensies. 'n Balans tussen die halfgeleier drywingsverliese en spanningskwalteit is behaal deur die skakel frekwensie in ag te neem in die beheer. 'n Voorspellinde-beheer algoritme om ‘n hoë toevoerkwaliteit te bereik en die drywingsverliese in die hoëdrywingshalfgeleier te beperk, deur skakel frekwensie te beheer, is bespreek vir 'n tap-geskakelde spanning reguleerder. Die toevoerkwaliteit, spanningsreguleerder topologie en die beheer algoritme word bespreek. Simulasie resultate van die uittree-spanning en stroom word getoon wanneer die beheer algoritme gebruik word om die omsetter te beheer. Hierdie resultate is deur praktiese metings op 'n sinkrone afkapper.

Made available in DSpace on 2016-12-12T20:27:38Z (GMT). No. of bitstreams: 1 Resumo - Eduardo Cavalca.pdf: 79555 bytes, checksum: 90f9b6daaa60256b513924a9a0d2ecdd (MD5) Previous issue date: 2013-07-12 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Model-based predictive control (MPC) approaches has been studied in a wide range of areas, as petrochemical and aerospace, mainly due to its capability of easily deal with physical and operational constraints. Moreover, such approaches can be extended for the application in control loops with nonlinear and time-variant systems. At this context, the objective of this work is to study some MPC techniques in order to evaluate their applicability to control a three-phase induction motor. More specifically, it was analyzed a Dynamic Matrix Control (DMC) approach, as well as two MPC techniques that uses state space modeling. The control algorithms in question and the nonlinear mathematical model of the motor in study were programmed using the free computing environment Scilab-Xcos®. The models of the threephase motor used in the MPC were obtained by a system identification method (based on the step response of the classical non-linear motor model) and by a phenomenological three-phase modeling approach. Multiple simulations have been performed considering variations in load and speed reference. Besides, some discussions are made related to the influence of the control parameters and about the computational cost. Finally, the results showed that the use of MPC techniques in induction machines has great potential. / Abordagens de controle preditivo baseado em modelo (MPC, do inglês model-based predictive control) têm sido estudadas em diversas áreas, como petroquímica e aeroespacial, principalmente devido à capacidade que apresentam em tratar restrições físicas e operacionais de forma simples. Além disso, tais abordagens podem ser estendidas para aplicação em malhas de controle de sistema não lineares e variantes no tempo. Nesse contexto o objetivo desse trabalho é estudar algumas técnicas de MPC a fim de avaliar sua aplicabilidade no controle de um motor de indução trifásico. Mais especificamente, é analisada a técnica DMC (do inglês Dynamic Matrix Control) bem como duas técnicas de MPC que utilizam modelos no espaço de estados. Os algoritmos de controle em questão e o modelo matemático não linear do motor estudado foram programados utilizando o Scilab-Xcos®, um ambiente de processamento de código livre. Os modelos do motor de indução trifásico utilizados no MPC foram obtidos por meio de um método de identificação de sistemas (baseado na resposta ao degrau do modelo clássico não linear do motor) e por uma abordagem de modelagem fenomenológica trifásica. Múltiplas simulações foram realizadas, considerando variações de carga e referência de velocidade, sendo então apresentadas algumas discussões sobre a influência dos parâmetros de controle e custo computacional. Finalmente, os resultados obtidos demonstraram que a aplicação de técnicas MPC em máquinas de indução apresenta um grande potencial.

Made available in DSpace on 2016-12-12T20:27:38Z (GMT). No. of bitstreams: 1 Aldo Zanella Junior.pdf: 3746857 bytes, checksum: 7ff548689a89fd8090402ad4891a23c1 (MD5) Previous issue date: 2015-07-09 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / This work introduces the report of performed studies in order to evaluate the applicability of generalized predictive control (GPC) to several plants. The main goal is to analyze the GPC performance in processes with different features, analyzing the influence of its tuning parameters. The study is justified by the fact that GPC presents itself as a generalized solution for several classes of processes, which are becoming increasingly complex and demanding for traditional controllers to handle. For the purpose to prove this proposal of GPC, it was performed several tests with plants of different orders and response characteristics, real and simulated, varying controller tuning parameters and measuring some quality indices. It was evaluated the influence of tuning parameters and it was made a report of conclusions that was reached. Through obtained results, it is shown that GPC satisfies the proposal and presents favorable results. / Esta dissertação traz o relato do estudo realizado a fim de avaliar a aplicabilidade do controlador preditivo generalizado (GPC) em plantas diversas. O objetivo principal é analisar o desempenho do GPC em processos com diferentes características, analisando a influência dos seus parâmetros de sintonia. O estudo se justifica pelo fato de que o GPC apresenta-se como uma solução generalizada para diversos tipos de processos, os quais estão se tornando cada vez mais complexos e com maiores exigências para o controlador. A fim de comprovar essa proposta do GPC, realizou-se inúmeros ensaios com plantas com respostas e ordem diferentes, reais e simuladas, variando-se os parâmetros de sintonia do controlador e medindo-se alguns parâmetros de qualidade. Avaliou-se a influência dos parâmetros de sintonia e fez-se um relato das conclusões a que se chegou. Através dos resultados obtidos, mostra-se que o GPC corresponde ao que se propõe para as plantas testadas e apresenta resultados favoráveis.

Nous observons ces dernières années un besoin grandissant dans l’industrie pour des robots capables d’interagir et de coopérer dans des environnements confinés. Cependant, aujourd’hui encore, la définition de trajectoires sûres pour les robots industriels doit être faite manuellement par l’utilisateur et le logiciel ne dispose que de peu d’autonomie pour réagir aux modifications de l’environnement. Cette thèse vise à produire une structure logicielle innovante pour gérer l’évitement d’obstacles en temps réel pour des robots manipulateurs évoluant dans des environnements dynamiques. Nous avons développé pour cela un algorithme temps réel de génération de trajectoires qui supprime de façon automatique l’étape fastidieuse de définition d’une trajectoire sûre pour le robot.La valeur ajoutée de cette thèse réside dans le fait que nous intégrons le problème de contrôle optimal dans le concept de hiérarchie de tâches pour résoudre un problème d’optimisation non-linéaire efficacement et en temps réel sur un système embarqué aux ressources limitées. Notre approche utilise une commande prédictive (MPC) qui non seulement améliore la réactivité de notre système mais présente aussi l’avantage de pouvoir produire une bonne approximation linéaire des contraintes d’évitement de collision. La stratégie de contrôle présentée dans cette thèse a été validée à l’aide de plusieurs expérimentations en simulations et sur systèmes réels. Les résultats démontrent l’efficacité, la réactivité et la robustesse de cette nouvelle structure de contrôle lorsqu’elle est utilisée dans des environnements dynamiques. / In the field of industrial robots, there is a growing need for having cooperative robots that interact with each other and share work spaces. Currently, industrial robotic systems still rely on hard coded motions with limited ability to react autonomously to dynamic changes in the environment. This thesis focuses on providing a novel framework to deal with real-time collision avoidance for robots performing tasks in a dynamic environment. We develop a reactive trajectory generation algorithm that reacts in real time, removes the fastidious optimization process which is traditionally executed by hand by handling it automatically, and provides a practical way of generating locally time optimal solutions.The novelty in this thesis is in the way we integrate the proposed time optimality problem in a task priority framework to solve a nonlinear optimization problem efficiently in real time using an embedded system with limited resources. Our approach is applied in a Model Predictive Control (MPC) setting, which not only improves reactivity of the system but presents a possibility to obtain accurate local linear approximations of the collision avoidance constraint. The control strategies presented in this thesis have been validated through various simulations and real-world robot experiments. The results demonstrate the effectiveness of the new control structure and its reactivity and robustness when working in dynamic environments.

Une structure de contrôle distribué partiellement coopérative est proposée dans cette thèse. La structure est consacrée au problème de commande d’un réseau composé de sous-systèmes non linéaires/linéaires qui sont interconnectés par leurs états et les entrées de commande. Par la coopération partielle, cela signifie que chaque sous-système est capable de préserver son propre objectif en utilisant un indice de la coopération ajustable qui définit dans quelle mesure il accepte de dégrader son propre niveau de performance afin d’aider ses voisins à maintenir leur intégrité sous les interconnexions potentiellement déstabilisantes. La communication entre les sous-systèmes est basée sur l’échange de niveaux de fonction de Lyapunov avec les contraintes associées et la quantité d’information transmise est plutôt réduite par rapport aux travaux les plus récents. Une autre caractéristique intéressante de cet structure de contrôle distribué non linéaire coopératif est l’utilisation de vecteurs prioritaires par chaque sous-système. Ce vecteur définit un ordre hiérarchique de l’importance de ses voisins menant à une stratégie de coopération dans lequel les sous-systèmes critiques dans le réseau peuvent être préservés en dépit des interactions. Une version linéaire de la structure de contrôle distribué coopératif est présenté. Cette conception de structure linéaire conduit à une évaluation rigoureuse de stabilité du réseau en boucle fermée globale. Une méthode d’amélioration de la stabilité est proposée basée sur la résolution d’un problème d’optimisation non convexe avec des degrés de liberté liés au paramétrage de l’affectation de priorité. Pour montrer son efficacité, le contrôle distribué coopératif proposé pour le réseau linéaire est appliqué pour traiter le problème de contrôle de la fréquence de charge dans un réseau d’alimentation et le problème de contrôle du système cryogénique. / In this dissertation, a partially cooperative distributed control framework is proposed. The framework is dedicated to the control problem for a network consisting of linear/nonlinear subsystems that are interconnected through their states and control inputs. By partial cooperation, it means that each subsystem is able to preserve its own objective while using a tunable cooperation index that defines to what extend it accepts to degrade its own performance level so as to help its neighbors maintain their integrity under potentially destabilizing interconnections. The communication between the subsystems is rather reduced comparing to most of the existing contributions. Another attractive feature of the proposed framework is that each subsystem in the network can be assigned with priority indicating the importance of the corresponding subsystem seen by its neighbors. Through proper parameterization of the priority assignment, improved performance of the subsystems and the network can be acheived. In the linear version, a rigorous stability assessment method is presented and a systematic way of proposing an optimized priority assignment for a given network is introduced as well. The proposed scheme is applied to handle the load frequency control problem in a 4-area power network and the control problem of a cryogenic system to illustrate its effectiveness.

L'énergie est une ressource clé dans les réseaux de capteurs sans fil (WSNs), en particulier lorsque les nœuds capteurs sont alimentés par des batteries. Cette thèse s'inscrit dans le contexte de la réduction de la consommation de l'énergie d'un réseau de capteurs au niveau application construite au-dessus de ce réseau, grâce à des stratégies de contrôle, en temps réel et de façon dynamique. La première stratégie de gestion de l'énergie considérée s'appuie sur le contrôle prédictif (MPC). Le choix de MPC est motivé par les objectifs globaux qui sont de réduire la consommation d'énergie de l'ensemble des nœuds capteurs tout en assurant un service donné, nommé mission, pour le réseau de capteurs. En outre, un ensemble de contraintes sur les variables de contrôle binaires et sur les nœuds capteur doit être rempli. La deuxième stratégie de gestion de l'énergie au niveau de l'application utilise une approche de contrôle hybride (HDS). Ce choix est motivé par la nature inhérente du système WSN qui est par essence hybride, en particulier lorsque l'on s'intéresse à la gestion de l'énergie. La nature hybride vient essentiellement de la combinaison de processus physiques continus tels la charge et décharge des batteries des nœuds; tandis que la partie discrète est liée à la modification des modes de fonctionnement et l'état Inaccessible des nœuds. Les stratégies proposées sont évaluées et comparées en simulation sur des différents scenarios réalistes. Elles ont aussi \'et\'e mises en œuvre sur un banc d'essai réel et les résultats obtenus ont été discutés. / Energy is a key resource in Wireless Sensor Networks (WSNs), especially when sensor nodes are powered by batteries. This thesis is investigates how to save energy of the whole WSN, at the application level, thanks to control strategies, in real time and in a dynamic way. The first energy management strategy investigated is based on Model Predictive Control (MPC). The choice of MPC is motivated by the global objectives that are to reduce the energy consumption of the set of sensor nodes while ensuring a given service, named mission, for the sensor network. Moreover, a set of constraints on the binary control variables and on the sensor modes must be fulfilled. The second energy management strategy at the application level is based on a Hybrid Dynamical System (HDS) approach. This choice is motivated by the hybrid inherent nature of the WSN system when energy management is considered. The hybrid nature basically comes from the combination of continuous physical processes, namely, the charge / discharge of the node batteries; while the discrete part is related to the change in the functioning modes and the Unreachable condition of the nodes. The proposed strategies are evaluated and compared in simulation on a realistic test-case. Lastly, they have been implemented on a real test-bench and the results obtained have been discussed.

Constraint handling is difficult in model predictive control (MPC) of linear differential inclusions (LDIs) and linear parameter varying (LPV) systems. The designer is faced with a choice of using conservative bounds that may give poor performance, or accurate ones that require heavy online computation. This thesis presents a framework to achieve a more flexible trade-off between these two extremes by using a state tube, a sequence of parametrised polyhedra that is guaranteed to contain the future state. To define controllers using a tube, one must ensure that the polyhedra are a sub-set of the region defined by constraints. Necessary and sufficient conditions for these subset relations follow from duality theory, and it is possible to apply these conditions to constrain predicted system states and inputs with only a little conservatism. This leads to a general method of MPC design for uncertain-parameter systems. The resulting controllers have strong theoretical properties, can be implemented using standard algorithms and outperform existing techniques. Crucially, the online optimisation used in the controller is a convex problem with a number of constraints and variables that increases only linearly with the length of the prediction horizon. This holds true for both LDI and LPV systems. For the latter it is possible to optimise over a class of gain-scheduled control policies to improve performance, with a similar linear increase in problem size. The framework extends to stochastic LDIs with chance constraints, for which there are efficient suboptimal methods using online sampling. Sample approximations of chance constraint-admissible sets are generally not positively invariant, which motivates the novel concept of ‘sample-admissible' sets with this property to ensure recursive feasibility when using sampling methods. The thesis concludes by introducing a simple, convex alternative to chance-constrained MPC that applies a robust bound to the time average of constraint violations in closed-loop.