The Final Oral Examination for

Networked control systems (NCSs) present many advantages such as easy installation and maintenance, flexible layouts and structures of components, and efficient allocation and distribution of resources. Consequently, they find potential applications in a variety of emerging industrial systems including multi-agent systems, power grids, tele-operations and cyberphysical systems. The study of NCSs with nonlinear dynamics (i.e., nonlinear NCSs) is a very significant yet challenging topic, and it not only widens application areas of NCSs in practice, but also extends the theoretical framework of NCSs with linear dynamics (i.e., linear NCSs). Numerous issues are required to be resolved towards a fully-fledged theory of industrial nonlinear NCS design. In this dissertation, three important problems are investigated: The robust filtering problem of uncertain nonlinear NCSs; the robust model predictive control (MPC) problem of nonlinear NCSs; the robust distributed MPC problem of large-scale nonlinear systems. In the robust filtering problem of nonlinear NCSs, the nonlinear system dynamics considered are subject to model uncertainties and external disturbances, and the measurements suffer from time delays governed by a Markov process. A robust H_infty nonlinear filter is designed such that the resulting filtering system achieves the mean-square stability and the prescribed disturbance attenuation level. Utilizing the augmentation technique and Lyapunov theory, a Markov chain-dependent algebraic Hamilton-Jacobi inequality (HJI) is established to guarantee stability. Moreover, the developed results are specialized for a special class of nonlinear systems, by presenting the HJI in terms of matrix inequalities. For the robust MPC problem of NCSs, three different aspects are considered. Firstly, the MPC-based networked control problem for constrained nonlinear NCSs subject to disturbances and two-channel packet dropouts is investigated. An efficient transmission and compensation mechanism has been designed such that all the necessary information is transmitted with reduced transmission load. A novel Lyapunov function has been constructed to ensure the regional input-to-state practical stability (ISpS) of the closed-loop system. Secondly, a class of constrained nonlinear NCSs subject to external disturbances, input and state constraints, and network induced constraints are studied. From a practical perspective, the network-induced constraints considered include the time delays and packet dropouts on both the sensor-tocontroller (S-C) and the controller-to-actuator (C-A) channels simultaneously. To improve robustness and control accuracy, a networked min-max MPC scheme which incorporates external disturbances into optimization problems is designed. The ISpS of the resulting nonlinear NCS is established by constructing a new Lyapunov function. Finally, the robust output feedback MPC problem for constrained linear systems subject to periodical measurement losses and external disturbances is explored. An observer is first designed such that the estimation error is bounded within a compact set. By utilizing the bounds of estimation error and the external disturbances to tighten the input and state constraints, the output feedback MPC algorithm is developed. The feasibility and stability issues are rigorously analyzed. For the robust distributed MPC problem of large-scale nonlinear systems, three steps are taken in order to conduct the studies. In the first step, the subsystems considered are subject to control input constraints and external disturbances, but without communication delays among them. A robustness constraint is proposed to handle the external disturbances, based on which a novel robust distributed MPC algorithm is designed. The feasibility of the robust distributed MPC algorithm and the robust stability of the overall agent system are analyzed. The conditions under which the proposed algorithm is feasible and the overall agent system is robustly stabilized are also developed. In the second step, the subsystems studied are subject to control input constraints and communication delays among them, but without external disturbances. By designing the waiting mechanism, a delay-involved distributed MPC scheme is proposed. The iterative feasibility and stability properties are analyzed. Based on the results in the first and second steps, the robust distributed MPC problem for large-scale nonlinear systems subject to control input constraints, communication delays and external disturbances are studied in the third step. A dual-mode robust distributed MPC strategy is designed to deal with the communication delays and the external disturbances simultaneously. The feasibility of the proposed distributed MPC algorithm and the stability of the closed-loop system are analyzed, and the sufficient conditions for ensuring the feasibility and stability are developed, respectively. It is shown that: (1) The feasibility is affected by the bounds of external disturbances, the sampling period and the bound of communication delays; (2) the stability is related to the bounds of external disturbances, the sampling period, the bound of communication delays and the minimum eigenvalues of the cooperation matrices; (3) the system state of the closed-loop system can be stabilized into a robustly invariant set under the proposed conditions. Awards, Scholarships, Fellowships 2012 Dr. Esme Foord Graduate Scholarship 2011 Student Travel Award, IEEE Control System Society 2011 Graduate Travel Grant, University of Victoria 2011 Mr. Alfred Smith and Mrs. Mary Anderson Smith Scholarship 2010 Graduate Fellowship, University of Victoria