Este trabalho aborda o problema de controle baseado em eventos para sistemas em tempo discreto, considerando que o sistema possui os dispositivos atuadores e sensores em nós diferentes e separados por uma rede de comunicação. A estratégia baseada em eventos consiste em reduzir a utilização da rede ao transmitir as informações do sensor para o atuador apenas quando um evento é gerado pela violação de um determinado limiar pela função de disparo. Primeiramente, são formuladas condições para a estabilidade de um sistema linear com realimentação estática de estados sob a estratégia proposta, com base na teoria de Lyapunov. Como as condições são postas na forma de desigualdades matriciais lineares (LMIs, do inglês linear matrix inequalities), problemas de otimização convexos podem ser utilizados na determinação dos parâmetros da função de disparo, bem como na resolução do problema de co-design, ou seja, do projeto simultâneo do controlador e da função de disparo, os quais são providos na sequência. A partir deste resultado básico, a metodologia é estendida para o caso em que ocorre a saturação do atuador. A seguir, é apresentada a extensão da metodologia para o caso em que o estado da planta não está disponível para o sensor, sendo então utlizado um observador de estados, considerando-se tanto o caso em que o modelo da planta utilizado no observador corresponde exatamente à dinâmica real da planta quanto o caso em que este modelo apresenta incertezas. Exemplos numéricos são apresentados para ilustrar todas as classes de sistemas consideradas, com os quais constata-se que a estratégia proposta é eficiente na redução da utilização dos recursos da rede de comunicação. / This work approaches the problem of event-triggered control for discrete time systems, considering that the system has the actuator and sensor devices in different nodes, separated by a communication network. The event-triggered strategy consists in reducing the utilization of the network by only transmitting the information from the sensor to the actuator when an event is generated by the violation of a determined threshold by the trigger function. Firstly, conditions for the stability of a linear system with a static state feedback under the proposed strategy are formulated based on the Lyapunov theory. Since the conditions are given in the form of linear matrix inequalities (LMIs), convex optimization problems can be used for the determination of the trigger function parameters, as well as the co-design of the feedback gain and the trigger function, which are given next. From this basic result, the methodology is extended to the case where occurs the saturation of the actuator. Following, the extension of the methodlogy to the case in which the plant states are not available for measure is presented, and a state-observer is used, considering both the case that the plant model corresponds exactly to the real plant dynamics and the case where this model has uncertainties. Numeric examples are shown to illustrate all the system classes considered, with which it is found that the proposed strategy is efficient in the reduction of the network resources utilization.

Networked control systems (NCSs) are feedback control systems with the feedback control loops closed via network. The origin of the term NCSs is from industrial systems where the plant and controller are often connected through networks. The applications of NCSs cover a wide range of industries, for example, manufactory automation, domestic robots, aircraft, automobiles and tele-operations. The research activities in NCSs are focused on the following three areas: control of networks, control over networks and multi-agent systems. Control of networks is mainly concerned with the problem of how to efficiently utilize the network resource by controlling and routing the network data flows. Control over networks is mainly concerned with the design of feedback control strategies of control systems in which signals are transmitted through unreliable communication links. Multi-agent systems deal with two problems: how the topology of the network connections between each component influences global control goals and how to design local control law describing the behavior of each individual to achieve the global control goal of the whole systems. The objective in this thesis is to deal with control over networks and multi-agent systems. The most challenging problem in the control over networks field is that the unreliable communication channels can degrade system performance greatly. The main unreliable properties of networks are delays and packet loss. In order to deal with this problem, a Lyapunov-based method has been used to design the sampled-data stabilization control strategy for a networked single system by choosing proper delay and packet loss dependent Lyapunov functional candidates. Linear matrix inequality techniques have been used to find the sufficient and necessary conditions for the controller design. Furthermore, the consensus formation control problem of multiple robotic vehicle systems has been investigated. The consensus-based design scheme has been applied to the formation control of multiple wheeled mobile-robot group with a virtual leader. A novel delay-dependent Lyapunov functional candidate has been constructed to investigate the convergence of the system states. The proposed control strategy is experimentally implemented for multiple wheeled mobile robots under neighbor-to-neighbor information exchange with group communication delays involved. In conclusion, through the simulation results and experimental validations, the proposed new Lyapunov-based control methods can effectively deal with the networked control systems discussed in this thesis.

Modern industrial control systems use a multitude of spatially distributed sensors and actuators to continuously monitor and control physical processes. Information exchange among control system components is traditionally done through physical wires. The need to physically wire sensors and actuators limits flexibility, scalability and reliability, since the cabling cost is high, cable connectors are prone to wear and tear, and connector failures can be hard to isolate. By replacing some of the cables with wireless communication networks, costs and risks of connector failures can be decreased, resulting in a more cost-efficient and reliable system. Integrating wireless communication into industrial control systems is challenging, since wireless communication channels introduce imperfections such as stochastic delays and information losses. These imperfections deteriorate the closed-loop control performance, and may even cause instability. In this thesis, we aim at developing design frameworks that take these imperfections into account and improve the performance of closed-loop control systems. The thesis first considers the joint design of packet forwarding policies and controllers for wireless control loops where sensor measurements are sent to the controller over an unreliable and energy-constrained multi-hop wireless network. For a fixed sampling rate of the sensor, the co-design problem separates into two well-defined and independent subproblems: transmission scheduling for maximizing the deadline-constrained reliability and optimal control under packet losses. We develop optimal and implementable solutions for these subproblems and show that the optimally co-designed system can be obtained efficiently. The thesis continues by examining event-triggered control systems that can help to reduce the energy consumption of the network by transmitting data less frequently. To this end, we consider a stochastic system where the communication between the controller and the actuator is triggered by a threshold-based rule. The communication is performed across an unreliable link that stochastically erases transmitted packets. As a partial protection against dropped packets, the controller sends a sequence of control commands to the actuator in each packet. These commands are stored in a buffer and applied sequentially until the next control packet arrives. We derive analytical expressions that quantify the trade-off between the communication cost and the control performance for this class of event-triggered control systems. The thesis finally proposes a supervisory control structure for wireless control systems with time-varying delays. The supervisor has access to a crude indicator of the overall network state, and we assume that individual upper and lower bounds on network time-delays can be associated to each value of the indicator. Based on this information, the supervisor triggers the most appropriate controller from a multi-controller unit. The performance of such a supervisory controller allows for improving the performance over a single robust controller. As the granularity of the network state measurements increases, the performance of the supervisory controller improves at the expense of increased computational complexity. / <p>QC 20150504</p>

Wireless networks in industrial process control enable new system architectures and designs. However, wireless control systems can be severely affected by the imperfections of the communication links. This thesis proposes new methods to handle such imperfections by adding additional components in the control loop, or by adapting sampling intervals and control actions. First, the predictive outage compensator is proposed. It is a filter which is implemented at the receiver side of networked control systems. There it generates predicted samples when data are lost, based on past data. The implementation complexity of the predictive outage compensator is analyzed. Simulation and experimental results show that it can considerably improve the closed-loop control performance under communication losses. The thesis continues with presenting an algorithm for controlling multiple processes on a shared communication network, using adaptive sampling intervals. The methodology is based on model predictive control, where the controller jointly decides the optimal control signal to be applied as well as the optimal time to wait before taking the next sample. The approach guarantees conflict-free network transmissions for all controlled processes. Simulation results show that the presented control law reduces the required amount of communication, while maintaining control performance. The third contribution of the thesis is an event-triggered model predictive controller for use over a wireless link. The controller uses open-loop optimal control, re-computed and communicated only when the system behavior deviates enough from a prediction. Simulations underline the methods ability to significantly reduce computation and communication effort, while guaranteeing a desired level of system performance. The thesis is concluded by an experimental validation of wireless control for a physical lab process. A hybrid model predictive controller is used, connected to the physical system through a wireless medium. The results reflect the advantages and challenges in wireless control. / <p>QC 20140217</p>

Designing local controllers for networked systems is challenging, because in these systems each local controller can often access only part of the overall information on system parameters and sensor measurements. Traditional control design cannot be easily applied due to the unconventional information patterns, communication network imperfections, and design procedure complexities. How to control large-scale systems is of immediate societal importance as they appear in many emerging applications, such as intelligent transportation systems, smart grids, and energy-efficient buildings. In this thesis, we make three contributions to the problem of designing networked controller under information asymmetries and limitations. In the first contribution, we investigate how to design local controllers to optimize a cost function using only partial knowledge of the model governing the system. Specifically, we derive some fundamental limitations in the closed-loop performance when the design of each controller only relies on local plant model information. Results are characterized in the structure of the networked system as well as in the available model information. Both deterministic and stochastic formulations are considered for the closed-loop performance and the available information. In the second contribution of the thesis, we study decision making in transportation systems using heterogeneous routing and congestion games. It is shown that a desirable global behavior can emerge from simple local strategies used by the drivers to choose departure times and routes. Finally, the third contribution is a novel stochastic sensor scheduling policy for ad-hoc networked systems, where a varying number of control loops are active at any given time. It is shown that the policy provides stochastic guarantees for the network resources dynamically allocated to each loop. / <p>QC 20140221</p>

Ο σκοπός αυτής της διπλωματικής εργασίας είναι να συζητηθούν και να παρουσιαστούν οι υπάρχουσες τεχνικές που εφαρμόζουν την στρατηγική δειγματοληψίας βασισμένη σε γεγονότα για την εκτίμηση της κατάστασης των γραμμικών συστημάτων και να αξιολογηθεί πώς αυτές οι μέθοδοι επηρεάζουν τη συνολική απόδοση του συστήματος. Όπως ήδη αναφέρθηκε, περιορισμοί στον ρυθμό δειγματοληψίας ανακύπτουν στα NCS λόγω του περιορισμένου διαθέσιμου εύρους ζώνης. Αυτός ο περιορισμός στον αριθμό δειγμάτων επηρεάζει σαφώς το μέσο τετραγωνικό σφάλμα εκτίμησης, και η ερώτηση είναι πώς πρέπει να επιλέξουμε τις χρονικές στιγμές δειγματοληψίας προκειμένου να το ελαχιστοποιήσουμε. / The aim of this diploma thesis is to discuss and present existing techniques that apply event-triggered sampling to linear system state estimation, and to evaluate how these methods affect the overall performance of the system. As already mentioned, sampling rate constraints arise in NCS due to the limited bandwidth available. This restriction on the number of samples clearly affects the mean square estimation distortion error, and the question is how we should choose the sampling instants in order to minimize it.

<p>Distributed optimization methods allow us to decompose an optimization problem</p><p>into smaller, more manageable subproblems that are solved in parallel. For this</p><p>reason, they are widely used to solve large-scale problems arising in areas as diverse</p><p>as wireless communications, optimal control, machine learning, artificial intelligence,</p><p>computational biology, finance and statistics, to name a few. Moreover, distributed</p><p>algorithms avoid the cost and fragility associated with centralized coordination, and</p><p>provide better privacy for the autonomous decision makers. These are desirable</p><p>properties, especially in applications involving networked robotics, communication</p><p>or sensor networks, and power distribution systems.</p><p>In this thesis we propose the Accelerated Distributed Augmented Lagrangians</p><p>(ADAL) algorithm, a novel decomposition method for convex optimization prob-</p><p>lems with certain separability structure. The method is based on the augmented</p><p>Lagrangian framework and addresses problems that involve multiple agents optimiz-</p><p>ing a separable convex objective function subject to convex local constraints and</p><p>linear coupling constraints. We establish the convergence of ADAL and also show</p><p>that it has a worst-case O(1/k) convergence rate, where k denotes the number of</p><p>iterations.</p><p>Moreover, we show that ADAL converges to a local minimum of the problem</p><p>for cases with non-convex objective functions. This is the first published work that</p><p>formally establishes the convergence of a distributed augmented Lagrangian method</p><p>ivfor non-convex optimization problems. An alternative way to select the stepsizes</p><p>used in the algorithm is also discussed. These two contributions are independent</p><p>from each other, meaning that convergence of the non-convex ADAL method can</p><p>still be shown using the stepsizes from the convex case, and, similarly, convergence</p><p>of the convex ADAL method can be shown using the stepsizes proposed in the non-</p><p>convex proof.</p><p>Furthermore, we consider cases where the distributed algorithm needs to operate</p><p>in the presence of uncertainty and noise and show that the generated sequences of</p><p>primal and dual variables converge to their respective optimal sets almost surely. In</p><p>particular, we are concerned with scenarios where: i) the local computation steps</p><p>are inexact or are performed in the presence of uncertainty, and ii) the message</p><p>exchanges between agents are corrupted by noise. In this case, the proposed scheme</p><p>can be classified as a distributed stochastic approximation method. Compared to</p><p>existing literature in this area, our work is the first that utilizes the augmented</p><p>Lagrangian framework. Moreover, the method allows us to solve a richer class of</p><p>problems as compared to existing methods on distributed stochastic approximation</p><p>that consider only consensus constraints.</p><p>Extensive numerical experiments have been carried out in an effort to validate</p><p>the novelty and effectiveness of the proposed method in all the areas of the afore-</p><p>mentioned theoretical contributions. We examine problems in convex, non-convex,</p><p>and stochastic settings where uncertainties and noise affect the execution of the al-</p><p>gorithm. For the convex cases, we present applications of ADAL to certain popular</p><p>network optimization problems, as well as to a two-stage stochastic optimization</p><p>problem. The simulation results suggest that the proposed method outperforms</p><p>the state-of-the-art distributed augmented Lagrangian methods that are known in</p><p>the literature. For the non-convex cases, we perform simulations on certain simple</p><p>non-convex problems to establish that ADAL indeed converges to non-trivial local</p><p>vsolutions of the problems; in comparison, the straightforward implementation of the</p><p>other distributed augmented Lagrangian methods on the same problems does not</p><p>lead to convergence. For the stochastic setting, we present simulation results of</p><p>ADAL applied on network optimization problems and examine the effect that noise</p><p>and uncertainties have in the convergence behavior of the method.</p><p>As an extended and more involved application, we also consider the problem</p><p>of relay cooperative beamforming in wireless communications systems. Specifically,</p><p>we study the scenario of a multi-cluster network, in which each cluster contains</p><p>multiple single-antenna source destination pairs that communicate simultaneously</p><p>over the same channel. The communications are supported by cooperating amplify-</p><p>and-forward relays, which perform beamforming. Since the emerging problem is non-</p><p>convex, we propose an approximate convex reformulation. Based on ADAL, we also</p><p>discuss two different ways to obtain a distributed solution that allows for autonomous</p><p>computation of the optimal beamforming decisions by each cluster, while taking into</p><p>account intra- and inter-cluster interference effects.</p><p>Our goal in this thesis is to advance the state-of-the-art in distributed optimization by proposing methods that combine fast convergence, wide applicability, ease</p><p>of implementation, low computational complexity, and are robust with respect to</p><p>delays, uncertainty in the problem parameters, noise corruption in the message ex-</p><p>changes, and inexact computations.</p> / Dissertation

Este trabalho apresenta uma proposta de solução para compensar o atraso variável, característico de redes IP. O preditor de Smith é tradicionalmente usado para compensar atrasos, mas no caso deste tipo de rede um fator importante que pode degradar o controle do sistema são as grandes variações nos atrasos sofridos pelas mensagens. Para tratar este problema, este trabalho baseia-se na criação de uma estrutura de dados de armazenamento para a saída do preditor de Smith, possibilitando a comparação do valor de saída da planta com o valor adequado guardado na estrutura. Para determinação do valor correspondente, este está associado a um índice calculado com o tempo de roundtrip obtido de informações dos pacotes de dados proveniente da planta. Para se chegar a tal solução, foi analisada nas primeiras seções a influência do atraso em malhas de controle e posteriormente um estudo do estado da arte para tipos de controle sobre redes IP. Ao final é apresentada uma análise experimental, demonstrando resultados promissores da aplicação desta proposta. / This work presents a solution to compensate the varying delay, characteristic of IP networks. The Smith predictor is traditionally used to compensate delays but in this type of networks an other important factor that can destabilize the system is the large jitter of the delay. In order to solve this problem, the solution presented here is based on a data structure to save the output from the model of the plant used by the Smith predictor, that make possible to compare the output from the plant with the corresponding value in the structure. In order to take the correspondent value, it is associated to an index which is calculated with the roundtrip obtained from the informations in the packet arrived from the plant. In order to formulate this solution, it was analised in the first sections the influence of the delay in control systems and then a study of the state of art of the control systems over IP networks. At the end, an experimental analise to demonstrate the good result of the application of this solution is presented.

Este trabalho aborda o problema de controle baseado em eventos para sistemas em tempo discreto, considerando que o sistema possui os dispositivos atuadores e sensores em nós diferentes e separados por uma rede de comunicação. A estratégia baseada em eventos consiste em reduzir a utilização da rede ao transmitir as informações do sensor para o atuador apenas quando um evento é gerado pela violação de um determinado limiar pela função de disparo. Primeiramente, são formuladas condições para a estabilidade de um sistema linear com realimentação estática de estados sob a estratégia proposta, com base na teoria de Lyapunov. Como as condições são postas na forma de desigualdades matriciais lineares (LMIs, do inglês linear matrix inequalities), problemas de otimização convexos podem ser utilizados na determinação dos parâmetros da função de disparo, bem como na resolução do problema de co-design, ou seja, do projeto simultâneo do controlador e da função de disparo, os quais são providos na sequência. A partir deste resultado básico, a metodologia é estendida para o caso em que ocorre a saturação do atuador. A seguir, é apresentada a extensão da metodologia para o caso em que o estado da planta não está disponível para o sensor, sendo então utlizado um observador de estados, considerando-se tanto o caso em que o modelo da planta utilizado no observador corresponde exatamente à dinâmica real da planta quanto o caso em que este modelo apresenta incertezas. Exemplos numéricos são apresentados para ilustrar todas as classes de sistemas consideradas, com os quais constata-se que a estratégia proposta é eficiente na redução da utilização dos recursos da rede de comunicação. / This work approaches the problem of event-triggered control for discrete time systems, considering that the system has the actuator and sensor devices in different nodes, separated by a communication network. The event-triggered strategy consists in reducing the utilization of the network by only transmitting the information from the sensor to the actuator when an event is generated by the violation of a determined threshold by the trigger function. Firstly, conditions for the stability of a linear system with a static state feedback under the proposed strategy are formulated based on the Lyapunov theory. Since the conditions are given in the form of linear matrix inequalities (LMIs), convex optimization problems can be used for the determination of the trigger function parameters, as well as the co-design of the feedback gain and the trigger function, which are given next. From this basic result, the methodology is extended to the case where occurs the saturation of the actuator. Following, the extension of the methodlogy to the case in which the plant states are not available for measure is presented, and a state-observer is used, considering both the case that the plant model corresponds exactly to the real plant dynamics and the case where this model has uncertainties. Numeric examples are shown to illustrate all the system classes considered, with which it is found that the proposed strategy is efficient in the reduction of the network resources utilization.

A importância das redes de comunicação industriais em modernos sistemas de automação e controle industriais tem aumentado significativamente nos últimos anos, devido aos avanços nas áreas de processadores e softwares embarcados, que permitem o desenvolvimento de dispositivos com elevada capacidade de processamento a custos reduzidos. Estas características também são muito importantes em sistemas automotivos, visto que existe uma tendência para a substituição de sistemas mecânicos e hidráulicos em veículos e o espaço disponível para implementação é bastante reduzido. Esta substituição passa pela elaboração de complexos algoritmos de controle, os quais, quando operam sobre uma rede de comunicação, precisam considerar explicitamente os efeitos do canal de comunicação compartilhado na dinâmica do sistema em malha fechada. Este trabalho apresenta uma análise do impacto da comunicação em rede sobre sistemas de controle. Mais especificamente, analisa-se o comportamento do protocolo Flexray, recentemente desenvolvido por um consórcio de importantes empresas e que incorpora interessantes conceitos para escalonamento de mensagens síncronas e assíncronas. No trabalho foram realizados experimentos com três diferentes tipos de controladores aplicados ao estudo de caso de uma suspensão ativa, onde o sistema tem sua malha fechada sobre a rede FlexRay. / The importance of communication networks on modern automation systems has increased significantly over the last years, mostly due to advances in embedded microprocessor and software technologies, which enable the development of devices with high processing power at reduced costs. These characteristics are very important for vehicle systems, since there is nowadays a trend to replace mechanical and hydraulic systems, and the space available for implementation is limited. This replacement requires very complex control algorithms, which, when operating on a communication network, have to consider explicitly the effects introduced by the shared communication channel on the closed loop system dynamics. This work presents an analysis of the network communication impact over control systems. More specifically, it is of interest to analyse the behavior of the FlexRay protocol, which has been recently developed by a Consortium of important companies and incorporates interesting concepts of synchronous and asynchronous message scheduling. In this work, some experiments were performed with three controllers, which were developed using different methodologies, applied to the case study of an active suspension system, where the loop is closed over the FlexRay protocol.