The eigenstructure assignment scheme for robust multivariable feedback control is extended to redundantly actuated dynamical systems. It is shown that an orthonormal set of close loop eigenvectors is always exactly assignable in the case of redundant actuation proving the inherent robustness in the control design methodology. A choice of close loop eigenvector set to minimize the feedback gain matrix is suggested. Partial Eigenstructure Assignment methodology is proposed for second order mechanical systems. A methodology for coordinated actuation of redundant actuator sets by a trained weighted minimum norm solution is presented. To apply the methodology to hyper-redundant actuator arrays, for application to smart actuator arrays, a novel adaptive discretization algorithm is proposed. The adaptive aggregation strategy, based on the physics of the system, introduces nodes, to optimize a performance index of the overall plant model. The dimensionality of the inputs thus reduces to a finite number, making it a candidate plant for control by the robust redundant control scheme. The adaptive aggregation together with robust redundant control methodology is demonstrated on a finite element model of a novel morphing wing. This schema unifies the traditionally disparate methods of modeling and controller design.

This thesis is an effort to develop closed-loop control strategies on computer networks and study their stability in the presence of network delays and packet losses. An algorithm using predictors was designed to ensure the system stability in presence of network delays and packet losses. A single actuator magnetic ball levitation system was used as a test bed to validate the proposed algorithm. A brief study of real-time requirements of the networked control system is presented and a client-server architecture is developed using real-time operating environment to implement the proposed algorithm. Real-time performance of the communication on Ethernet based on user datagram protocol (UDP) was explored and UDP is presented as a suitable protocol for networked control systems. Predictors were designed based on parametric estimation models. Autoregressive (AR) and autoregressive moving average (ARMA) models of various orders were designed using MATLAB and an eighth order AR model was adopted based on the best-fit criterion. The system output was predicted several steps ahead using these predictors and control output was calculated using the predictions. This control output output was used in the events of excessive network delays to maintain system stability. Experiments employing simulations of consecutive packet losses and network delays were performed to validate the satisfactory performance of the predictor based algorithm. The current system compensates for up to 20 percent data losses in the network without loosing stability.

<p>Development of the World Wide Web makes it possible for multiple computers to work together in order to solve problems and make the most efficient use of resources. A distributed system is composed of such computers which are separately located and connected with each other through a network. One paradigm for computation using distributed systems is the multi-agent systems, in which many autonomous agents interact with each other to solve problems. The agents in a multi-agent system may be distributed on different computers (or nodes), where each computer owns its resources. Although the resources in a multi-agent system are connected by a network through which mobile agents can migrate for accessing sufficient resources, how to share these independently owned resources in both an effective and an efficient way is not fully understood. A key challenge in multi-agent systems is how to account for and control the resources which are located on individual nodes.</p> <p>The CyberOrgs model offers one approach to manage resources among competitive or collaborative agents by organizing computations and resources in a hierarchy. A cyberorg encapsulates agents and resources in a boundary and distributes the resources available to it within this boundary. A cyberorg contained in another cyberorg has a contract with the outer cyberorg, according to which it receives resources that it may use. A cyberorg also encapsulates an amount of the eCash, which is the currency for purchasing resources from its host cyberorg. Therefore, cyberorgs have a hierarchical structure in which resources are delivered to computations by a process where resources flow down from the root to the leaves of the hierarchy and the eCash flows up from the leaves toward the root. However, the hierarchical structure of the CyberOrgs model presents challenges in scalability. As a result, efficiency is an important concern in the implementation of CyberOrgs.</p> <p>In this thesis, an efficient implementation of the CyberOrgs model is described. System design, APIs of the implementation, example applications, experimental results, and future directions are presented.</p>

<p>Development of the World Wide Web makes it possible for multiple computers to work together in order to solve problems and make the most efficient use of resources. A distributed system is composed of such computers which are separately located and connected with each other through a network. One paradigm for computation using distributed systems is the multi-agent systems, in which many autonomous agents interact with each other to solve problems. The agents in a multi-agent system may be distributed on different computers (or nodes), where each computer owns its resources. Although the resources in a multi-agent system are connected by a network through which mobile agents can migrate for accessing sufficient resources, how to share these independently owned resources in both an effective and an efficient way is not fully understood. A key challenge in multi-agent systems is how to account for and control the resources which are located on individual nodes.</p> <p>The CyberOrgs model offers one approach to manage resources among competitive or collaborative agents by organizing computations and resources in a hierarchy. A cyberorg encapsulates agents and resources in a boundary and distributes the resources available to it within this boundary. A cyberorg contained in another cyberorg has a contract with the outer cyberorg, according to which it receives resources that it may use. A cyberorg also encapsulates an amount of the eCash, which is the currency for purchasing resources from its host cyberorg. Therefore, cyberorgs have a hierarchical structure in which resources are delivered to computations by a process where resources flow down from the root to the leaves of the hierarchy and the eCash flows up from the leaves toward the root. However, the hierarchical structure of the CyberOrgs model presents challenges in scalability. As a result, efficiency is an important concern in the implementation of CyberOrgs.</p> <p>In this thesis, an efficient implementation of the CyberOrgs model is described. System design, APIs of the implementation, example applications, experimental results, and future directions are presented.</p>

This thesis is an e&#64256;ort to develop closed-loop control strategies on computer networks and study their stability in the presence of network delays and packet losses. An algorithm using predictors was designed to ensure the system stability in presence of network delays and packet losses. A single actuator magnetic ball levitation system was used as a test bed to validate the proposed algorithm. A brief study of real-time requirements of the networked control system is presented and a client-server architecture is developed using real-time operating environment to implement the proposed algorithm. Real-time performance of the communication on Ethernet based on user datagram protocol (UDP) was explored and UDP is presented as a suitable protocol for networked control systems. Predictors were designed based on parametric estimation models. Autoregressive (AR) and autoregressive moving average (ARMA) models of various orders were designed using MATLAB and an eighth order AR model was adopted based on the best-&#64257;t criterion. The system output was predicted several steps ahead using these predictors and control output was calculated using the predictions. This control output output was used in the events of excessive network delays to maintain system stability. Experiments employing simulations of consecutive packet losses and network delays were performed to validate the satisfactory performance of the predictor based algorithm. The current system compensates for up to 20 percent data losses in the network without loosing stability.

The major objective of this dissertation is extending the capabilities of game theoretic distributed control to more general settings. In particular, we are interested in drifting environments and/or constrained communications. The first part of the dissertation concerns slowly varying dynamics, i.e., drifting environments. A standard assumption in game theoretic learning is a stationary environment, e.g., the game is fixed. We investigate the case of slow variations and show that for sufficiently slow time variations, the limiting behavior “tracks” the stochastically stable states. Since the analysis is regarding Markov processes, the results could be applied to various game theoretic learning rules. In this research, the results were applied to log-linear learning. A mobile sensor coverage example was tested in both simulation and laboratory experiments. The second part considers a problem of coordinating team players' actions without any communications in team-based zero-sum games. Generally, some global signalling devices are required for common randomness between players, but communications are very limited or impossible in many practical applications. Instead of learning a one-shot strategy, we let players coordinate a periodic sequence of deterministic actions and put an assumption on opponent's rationality. Since team players' action sequences are periodic and deterministic, common randomness is no longer required to coordinate players. It is proved that if a length of a periodic action sequence is long enough, then opponents with limited rationality cannot recognize its pattern. Because the opponents cannot recognize that the players are playing deterministic actions, the players' behavior looks like a correlated and randomized joint strategy with empirical distribution of their action sequences. Consequently players can coordinate their action sequences without any communications or global signals, and the resulting action sequences have correlated behavior. Moreover, the notion of micro-players are introduced for efficient learning of long action sequences. Micro-player matching approach provides a new framework that converts the original team-based zero-sum game to a game between micro-players. By introducing a de Bruijn sequence to micro-player matching, we successfully separate the level of opponent's rationality and the size of the game of micro-players. The simulation results are shown to demonstrate the performance of micro-player matching methods. Lastly, the results of the previous two topics are combined by considering a problem of coordinating actions without communications in drifting environments. More specifically, it is assumed that the opponent player in the team-based zero-sum games tries to adjust its strategy in the set of bounded recall strategies. Then the time-varying opponent's strategy can be considered as a dynamic environment parameter in a coordination game between the team players. Additionally, we develop a human testbed program for further study regarding a human as an adaptive opponent in the team-based zero-sum games. The developed human testbed program can be a starting point for studying game theoretic correlated behavior learning against a human.

<p> The quasi-steady state optimization of a single tubular fixed bed chemical reactor with a slowly decaying catalyst is considered. The optimal choice of temperature T(z,t) distributed in both the space of the reactor and in chronological time is sought so as to maximize the total amount of reaction in a fixed given period of time. A single irreversible reaction is considered with a rate expressible as a product of separate functions of temperature, activity and conversion. The rate of catalyst decay is also a product of separate functions of temperature and activity but independent of conversion. Upper and lower bounds are placed on the permitted temperature. Theoretical characterization of the optimal policy is obtained using Sirazetdinov and Degtyarev's maximum principle derived for first-order partial differential equations and the influence of the ratio of reaction activation energy to catalyst deactivation energy on the derived optimal policy is indicated. Numerical calculations are presented to illustrate the optimal policies.</p> / Thesis / Doctor of Philosophy (PhD)

Quando se dispõe de um sistema de controle distribuído em tempo real, o atendimento aos requisitos temporais constitui-se num fator crucial para a aplicação. Assim, para garantir que tais requisitos sejam atendidos, é fundamental que o tráfego de mensagens no barramento seja gerenciado e controlado apropriadamente, evitando-se atrasos na comunicação para não prejudicar a performance do sistema e do produto final. Este trabalho apresenta um mestre PROFIBUS desenvolvido em PC, cujas finalidades foram analisar por meio de dados experimentais, a influência do parâmetro TTR no tempo de atualização das variáveis de processo no sistema e o tempo de reintegração da estação-mestre no anel lógico após perda de mensagem de token. / Using a real-time distributed control system, it is crucial to fullfill the time requirements for an application. Therefore, to guarantee that these requirements are fulfilled, it is essential to manage and control the message traffic in the bus properly, avoiding delays in the communication that could compromise the final product and the system performance. This study presents a PROFIBUS master based on PC. The main purpose of the PROFIBUS master is to analyze, using empirical data, the influence of the TTR parameter in the updating time of the process variables and the time interval to reintegrate a master device to the logical ring after a token message is lost.

Quando se dispõe de um sistema de controle distribuído em tempo real, o atendimento aos requisitos temporais constitui-se num fator crucial para a aplicação. Assim, para garantir que tais requisitos sejam atendidos, é fundamental que o tráfego de mensagens no barramento seja gerenciado e controlado apropriadamente, evitando-se atrasos na comunicação para não prejudicar a performance do sistema e do produto final. Este trabalho apresenta um mestre PROFIBUS desenvolvido em PC, cujas finalidades foram analisar por meio de dados experimentais, a influência do parâmetro TTR no tempo de atualização das variáveis de processo no sistema e o tempo de reintegração da estação-mestre no anel lógico após perda de mensagem de token. / Using a real-time distributed control system, it is crucial to fullfill the time requirements for an application. Therefore, to guarantee that these requirements are fulfilled, it is essential to manage and control the message traffic in the bus properly, avoiding delays in the communication that could compromise the final product and the system performance. This study presents a PROFIBUS master based on PC. The main purpose of the PROFIBUS master is to analyze, using empirical data, the influence of the TTR parameter in the updating time of the process variables and the time interval to reintegrate a master device to the logical ring after a token message is lost.

Les systèmes multi-agents sont des systèmes dynamiques composés par plusieurs éléments qui interagissent entre eux. Ces éléments sont appelés agents. Un agent est un système dynamique caractérisé par deux propriétés. La première est que les agents sont autonomes— c’est-à-dire qu’ils ne sont pas dirigés par l’environnement extérieur et ils peuvent évoluer selon un comportement auto-organisé. La seconde est que les agents sont capables de communiquer entre eux pour accomplir des tâches complexes, telles que la coopération, la coordination et la résolution de conflits. L’un des problèmes courants concernant les systèmes multi-agents est la synchronisation. Les agents sont synchronisés lorsque leur évolution dans le temps converge vers une trajectoire commune. Plusieurs applications du monde réel peuvent être conceptualisés comme des problèmes de synchronisation des systèmes multi-agents : par exemple, l’alignement en vitesse ( flocking en anglais), et le contrôle de la formation du mouvement de groupes cohérents. La synchronisation des systèmes multi-agents peut être obtenue grâce à différentes techniques de contrôle. Dans cette thèse nous proposons des méthodes de contrôle centralisées et distribuées pour la synchronisation des systèmes multi-agents. Nous développons des conditions nécessaires et suffisantes pour la synchronisation des systèmes multi-agents, composés par des agents identiques et linéaires qui ne changent pas dans le temps, en utilisant une approche Lyapunov. Ces conditions sont utilisées pour la conception de lois de contrôles distribuées. ensuite, nous étendons les résultats aux systèmes multi-agents soumis à des perturbations externes, assurant un niveau de performance désiré grâce à une technique de contrôle de type 퐻 ∞ . enfin, nous étendons l’analyse aux systèmes multi-agents avec contraintes sur les actionneurs, en utilisant des techniques de contrôle anti-windup. Nous évaluons l’efficacité et les performances des stratégies de contrôle proposées dans plusieurs simulations, dont deux d’entre elles sont inspirées par des applications issues du monde réel. La première est le contrôle du vol en formation d’avions, et la seconde est l’analyse de la transmission de contenus vidéo comme un problème de synchronisation. Nous comparons aussi les résultats obtenus avec des techniques de contrôle alternatives. / Multi-agent systems are dynamical systems composed of multiple interacting elements known as agents . Each agent is a dynamical system with two characteristics. First, it is capable of autonomous action—that is, it is able to evolve according to a self-organised behavior, which is not influenced by the external environment. Second, it is able to exchange information with other agents in order to accomplish complex tasks, such as coordination, cooperation, and conflict resolution. One commonly studied problem in multi-agent systems is synchronization. The agents are synchronized when their time evolutions converge to a common trajectory. Many real-world applications, such as flocking and formation control, can be cast as synchronization problems. Agent synchronization can be achieved using different approaches. In this thesis, we propose distributed and centralized control paradigms for the synchronization of multi-agent systems. We develop necessary and sufficient conditions for the synchronization of multi-agent systems, composed by identical linear time-invariant agents, us- ing a Lyapunov-based approach. Then we use these conditions to design distributed synchronization controllers. Then, we extend this result to multi-agent systems subject to external disturbances enforcing disturbance rejection with 퐻 ∞ control techniques. Furthermore, we extend the analysis to multi-agent systems with actuator constraints using LMI-based anti-windup techniques. We test the proposed control design strategies in simulated examples among which two are inspired by real-world applications. In the first, we study airplane formation control as a synchronization problem. In the second, we analyze the delivery of video streams as a synchronization problem and we compare the results to existing controllers.