Control over wireless sensor and actuator networks is of growing interest in process industry since it enables flexible design, deployment, operation, and maintenance. An important problem in industrial wireless control is how to limit the amount of information that needs to be exchanged over the network. In this thesis, network scheduling and remote control co-design is considered to address this problem. In the first part, we propose a design of an optimal network schedule for state estimation over a multi-hop wireless sensor network. We formulate an optimization problem, minimizing a linear combination of the averaged estimation error and transmission energy. A periodic network schedule is obtained, which specifies when and through which routes each sensor in the network should transmit its measurement, so that an optimal remote estimate under sensor energy consideration is achieved. We also propose some suboptimal schedules to reduce the computational load. The effectiveness of the suboptimal schedules is evaluated in numerical examples. In the second part, we propose a co-design framework for sensor scheduling, routing, and control over a multi-hop wireless sensor and actuator network. For a decoupled plant and LQG control performance, we formulate an optimization problem and show that the optimal schedule, routing, and control can be obtained locally for each control loop. In this part, we also introduce algorithms to reconfigure the schedules and routes when a link in the network is disconnected. The results are illustrated in a numerical example. In the third part, we consider event-based feedforward control from a wireless disturbance sensor. We derive stability conditions when the closed-loop system is subject to actuator saturation. Feedforward control with anti-windup compensation is introduced to reduce the effect of actuator saturation. The effectiveness of the approach is illustrated in some numerical examples. / <p>QC 20181029</p>

Made available in DSpace on 2014-12-17T15:48:05Z (GMT). No. of bitstreams: 1 PriscillaVD_DISSERT.pdf: 2033070 bytes, checksum: 27c8a6f6a0e802c19b0f74553cc6db23 (MD5) Previous issue date: 2012-09-28 / The field of Wireless Sensor and Actuator Networks (WSAN) is fast increasing and has attracted the interest of both the research community and the industry because of several factors, such as the applicability of such networks in different application domains (aviation, civil engineering, medicine, and others). Moreover, advances in wireless communication and the reduction of hardware components size also contributed for a fast spread of these networks. However, there are still several challenges and open issues that need to be tackled in order to achieve the full potential of WSAN usage. The development of WSAN systems is one of the most relevant of these challenges considering the number of variables involved in this process. Currently, a broad range of WSAN platforms and low level programming languages are available to build WSAN systems. Thus, developers need to deal with details of different sensor platforms and low-level programming abstractions of sensor operational systems on one hand, and they also need to have specific (high level) knowledge about the distinct application domains, on the other hand. Therefore, in order to decouple the handling of these two different levels of knowledge, making easier the development process of WSAN systems, we propose LWiSSy (Domain Language for Wireless Sensor and Actuator Networks Systems), a domain specific language (DSL) for WSAN. The use of DSLs raises the abstraction level during the programming of systems and modularizes the system building in several steps. Thus, LWiSSy allows the domain experts to directly contribute in the development of WSANs without having knowledge on low level sensor platforms, and network experts to program sensor nodes to meet application requirements without having specific knowledge on the application domain. Additionally, LWiSSy enables the system decomposition in different levels of abstraction according to structural and behavioral features and granularities (network, node group and single node level programming) / As Redes de Sensores e Atuadores Sem Fio (RSASF) v?m emergindo rapidamente e t?m atra?do o interesse da comunidade de pesquisa e da ind?stria, gra?as a v?rios fatores, dentre eles a aplicabilidade desse tipo de rede nos mais diversos dom?nios de aplica??es (avia??o, engenharia civil, medicina, dentre outros). Al?m disso, avan?os na comunica??o sem fio e miniaturiza??o dos componentes de hardware tamb?m contribu?ram para a r?pida prolifera??o dessas redes. Apesar disso, ainda existem alguns desafios a serem transpostos a fim de se atingir o pleno potencial de utiliza??o das RSASF. Dentre estes, o desenvolvimento de sistemas de RSASF aparece como um dos mais relevantes atualmente, haja vista a quantidade de vari?veis envolvidas no processo de desenvolvimento. Atualmente, uma vasta gama de plataformas de RSASF e diversas linguagens de programa??o de baixo n?vel podem ser empregadas no desenvolvimento desses sistemas. Dessa forma, ? necess?rio que o desenvolvedor possua tanto conhecimento de baixo n?vel relativo ? plataforma da RSASF, quanto conhecimento espec?fico do dom?nio de cada uma das aplica??es presentes no sistema. A fim de efetuar o desacoplamento da utiliza??o destes conhecimentos durante o processo de desenvolvimento, de forma a facilitar tal processo, este trabalho prop?e LWiSSy (Domain Language for Wireless Sensor and Actuator Networks Systems), uma linguagem para modelagem de sistemas para RSASF baseada no uso de DSLs (Domain Specific Language). As DSLs, pelo fato de aumentarem o n?vel de abstra??o da programa??o e modularizarem a constru??o de sistemas em v?rias etapas, permitir?o que ambos os especialistas envolvidos (dom?nio e redes) possam contribuir diretamente durante o desenvolvimento do sistema e de maneira mais desacoplada do que ocorre atualmente. Al?m dos benef?cios supracitados, LWiSSy possibilitar? ainda a decomposi??o do sistema em diferentes n?veis de abstra??o, haja vista a necessidade de representar diferentes caracter?sticas (estrutural e comportamental) e granulosidades (programa??o em n?vel de rede, em n?vel de grupos de n?s e em n?vel de n?) em um ?nico sistema