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.

The use of communication networks in digital control systems introduces stability and reliability concerns. Standard reliability and safety assessment methods need further modification to accommodate the issue in the reliability assessment of networked control systems. In this thesis, it is demonstrated that the Dynamic Flowgraph Methodology (DFM) can be extended to model networked control systems. The modelling of the communication network influence on the performance of the control system is presented. The areas that can affect the reliability of the control system are identified using the methodology. The thesis also presents the application of the DFM to a nuclear-based thermochemical water splitting process for hydrogen production, the Copper-Chlorine (Cu-Cl) cycle. The architecture of a networked control system and configuration of instrumentation and control systems for the hydrogen production plant are proposed in the thesis. / UOIT

Networked control systems (NCSs) are a kind of distributed control systems in which the data between control components are exchanged via communication networks. Because of the attractive advantages of NCSs such as reduced system wiring, low weight, and ease of system diagnosis and maintenance, the research on NCSs has received much attention in recent years. The first part (Chapter 2 - Chapter 4) of the thesis is devoted to designing new controllers for NCSs by incorporating the network-induced delays. The thesis also conducts research on filtering of multirate systems and identification of Hammerstein systems in the second part (Chapter 5 - Chapter 6).<br /><br /> Network-induced delays exist in both sensor-to-controller (S-C) and controller-to-actuator (C-A) links. A novel two-mode-dependent control scheme is proposed, in which the to-be-designed controller depends on both S-C and C-A delays. The resulting closed-loop system is a special jump linear system. Then, the conditions for stochastic stability are obtained in terms of a set of linear matrix inequalities (LMIs) with nonconvex constraints, which can be efficiently solved by a sequential LMI optimization algorithm. Further, the control synthesis problem for the NCSs is considered. The definitions of <em>H₂</em> and <em>H_∞</em> norms for the special system are first proposed. Also, the plant uncertainties are considered in the design. Finally, the robust mixed <em>H₂/H_&infin;</em> control problem is solved under the framework of LMIs. <br /><br /> To compensate for both S-C and C-A delays modeled by Markov chains, the generalized predictive control method is modified to choose certain predicted future control signal as the current control effort on the actuator node, whenever the control signal is delayed. Further, stability criteria in terms of LMIs are provided to check the system stability. The proposed method is also tested on an experimental hydraulic position control system. <br /><br /> Multirate systems exist in many practical applications where different sampling rates co-exist in the same system. The <em>l₂-l_&infin;</em> filtering problem for multirate systems is considered in the thesis. By using the lifting technique, the system is first transformed to a linear time-invariant one, and then the filter design is formulated as an optimization problem which can be solved by using LMI techniques. <br /><br /> Hammerstein model consists of a static nonlinear block followed in series by a linear dynamic system, which can find many applications in different areas. New switching sequences to handle the two-segment nonlinearities are proposed in this thesis. This leads to less parameters to be estimated and thus reduces the computational cost. Further, a stochastic gradient algorithm based on the idea of replacing the unmeasurable terms with their estimates is developed to identify the Hammerstein model with two-segment nonlinearities. <br /><br /> Finally, several open problems are listed as the future research directions.

Networked control systems (NCSs) are a kind of distributed control systems in which the data between control components are exchanged via communication networks. Because of the attractive advantages of NCSs such as reduced system wiring, low weight, and ease of system diagnosis and maintenance, the research on NCSs has received much attention in recent years. The first part (Chapter 2 - Chapter 4) of the thesis is devoted to designing new controllers for NCSs by incorporating the network-induced delays. The thesis also conducts research on filtering of multirate systems and identification of Hammerstein systems in the second part (Chapter 5 - Chapter 6).<br /><br /> Network-induced delays exist in both sensor-to-controller (S-C) and controller-to-actuator (C-A) links. A novel two-mode-dependent control scheme is proposed, in which the to-be-designed controller depends on both S-C and C-A delays. The resulting closed-loop system is a special jump linear system. Then, the conditions for stochastic stability are obtained in terms of a set of linear matrix inequalities (LMIs) with nonconvex constraints, which can be efficiently solved by a sequential LMI optimization algorithm. Further, the control synthesis problem for the NCSs is considered. The definitions of <em>H₂</em> and <em>H_∞</em> norms for the special system are first proposed. Also, the plant uncertainties are considered in the design. Finally, the robust mixed <em>H₂/H_&infin;</em> control problem is solved under the framework of LMIs. <br /><br /> To compensate for both S-C and C-A delays modeled by Markov chains, the generalized predictive control method is modified to choose certain predicted future control signal as the current control effort on the actuator node, whenever the control signal is delayed. Further, stability criteria in terms of LMIs are provided to check the system stability. The proposed method is also tested on an experimental hydraulic position control system. <br /><br /> Multirate systems exist in many practical applications where different sampling rates co-exist in the same system. The <em>l₂-l_&infin;</em> filtering problem for multirate systems is considered in the thesis. By using the lifting technique, the system is first transformed to a linear time-invariant one, and then the filter design is formulated as an optimization problem which can be solved by using LMI techniques. <br /><br /> Hammerstein model consists of a static nonlinear block followed in series by a linear dynamic system, which can find many applications in different areas. New switching sequences to handle the two-segment nonlinearities are proposed in this thesis. This leads to less parameters to be estimated and thus reduces the computational cost. Further, a stochastic gradient algorithm based on the idea of replacing the unmeasurable terms with their estimates is developed to identify the Hammerstein model with two-segment nonlinearities. <br /><br /> Finally, several open problems are listed as the future research directions.

Networked Control Systems (NCS) are distributed control systems where the sensor signals to the controllers and the control data to the actuators are enclosed in messages and sent over a communication network. On the one hand, the design of an NCS requires ensuring the stability of the control system and achieving system response that is as close as possible to that of an ideal system which demands network resources. On the other hand, these resources are limited and have to be allocated efficiently to accommodate for future system extensions as well as applications other than control purpose. Furthermore the NCS design parameters for the control system messages and the message transmission over the network are interdependent. In this thesis, we propose &ldquo / Integrated NCS Design (INtERCEDE: Integrated NEtwoRked Control systEm DEsign)&rdquo / a novel algorithmic approach for the design of NCS which ensures the stability of the control system, brings system response to that of an ideal system v as close as desired and conserves network bandwidth at the same time. The core of INtERCEDE is a bargaining game approach which iteratively calculates the message parameters and network service parameters. Our experimental results demonstrate the operation of INtERCEDE and how it computes the optimal design parameters for the example NCS.

Der Trend auch für schnelle, zeitkritische Regelungsaufgaben geht zunehmend in Richtung Feldbusse und Industrial Ethernet. Dem unbestreitbaren Nutzen der Kosteneinsparung stehen Probleme gegenüber: Die unsicheren Zeitbedingungen im Netz verschlechtern die dynamischen Eigenschaften digitaler Regelungen in unvorhersehbarer Weise. Diese Arbeit stellt eine praktikable Methodik vor, um die Regelgüte solcher Systeme sicher und aufwandsarm vorherzusagen. / High dynamic, i.e. time-critical automatic feedback control systems are more and more implemented using field bus or industrial ethernet solutions. The cost-efficiency of these approaches is unchallengeable, but they also cause serious technical problems: Uncertain time behavior of data networks so far degrades the dynamic performance of digital closed-loop controls in an unpredictable manner. The research paper introduces a practicable, reliable and straightforward method to forecast the system behavior.

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>

The objective of this thesis is to develop decentralized methods for building robust multi-agent networks through self-organization. Multi-agent networks appear in a large number of natural and engineered systems, including but not limited to, biological networks, social networks, communication systems, transportation systems, power grids, and robotic swarms. Networked systems typically consist of numerous components that interact with each other to achieve some collaborative tasks such as flocking, coverage optimization, load balancing, or distributed estimation, to name a few. Multi-agent networks are often modeled via interaction graphs, where the nodes represent the agents and the edges denote direct interactions between the corresponding agents. Interaction graphs play a significant role in the overall behavior and performance of multi-agent networks. There- fore, graph theoretic analysis of networked systems has received a considerable amount of attention within the last decade. In many applications, network components are likely to face various functional or structural disturbances including, but not limited to, component failures, noise, or malicious attacks. Hence, a desirable network property is robustness, which is the ability to perform reasonably well even when the network is subjected to such perturbations. In this thesis, robustness in multi-agent networks is pursued in two parts. The first part presents a decentralized graph reconfiguration scheme for formation of robust interaction graphs. Particularly, the proposed scheme transforms any interaction graph into a random regular graph, which is robust to the perturbations of their nodes/links. The second part presents a decentralized coverage control scheme for optimal protection of networks by some mobile security resources. As such, the proposed scheme drives a group of arbitrarily deployed resources to optimal locations on a network in a decentralized fashion.

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>