Filtering and Model Predictive Control of Networked Nonlinear Systems

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dc.contributor.authorLi, Huiping
dc.contributor.supervisorShi, Yang
dc.date.accessioned2013-04-29T19:03:18Z
dc.date.available2013-04-29T19:03:18Z
dc.date.copyright2013en_US
dc.date.issued2013-04-29
dc.degree.departmentDept. of Mechanical Engineeringen_US
dc.degree.levelDoctor of Philosophy Ph.D.en_US
dc.description.abstractNetworked 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 cyber-physical 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 of nonlinear NCSs are investigated: The robust filtering problem, the robust model predictive control (MPC) problem and the robust distributed MPC problem of large-scale nonlinear systems. In the robust filtering problem of nonlinear NCSs, the nonlinear system model is subject to uncertainties and external disturbances, and the measurements suffer from time delays governed by a Markov process. Utilizing the Lyapunov theory, the algebraic Hamilton-Jacobi inequality (HJI)-based sufficient conditions are established for designing the H_infty nonlinear filter. Moreover, the developed results are specialized for a special type of nonlinear systems, by presenting the HJI in terms of matrix inequalities. For the robust MPC problem of NCSs, three aspects are considered. Firstly, to reduce the computation and communication load, the networked MPC scheme with an efficient transmission and compensation strategy is proposed, for constrained nonlinear NCSs with disturbances and two-channel packet dropouts. A novel Lyapunov function is constructed to ensure the input-to-state practical stability (ISpS) of the closed-loop system. Secondly, to improve robustness, a networked min-max MPC scheme are developed, for constrained nonlinear NCSs subject to external disturbances, input and state constraints, and network-induced constraints. The ISpS of the resulting nonlinear NCS is established by constructing a new Lyapunov function. Finally, to deal with the issue of unavailability of system state, a robust output feedback MPC scheme is designed for constrained linear systems subject to periodical measurement losses and external disturbances. The rigorous feasibility and stability conditions are established. For the robust distributed MPC problem of large-scale nonlinear systems, three steps are taken to conduct the studies. In the first step, the issue of external disturbances is addressed. A robustness constraint is proposed to handle the external disturbances, based on which a novel robust distributed MPC algorithm is designed. The conditions for guaranteeing feasibility and stability are established, respectively. In the second step, the issue of communication delays are dealt with. By designing the waiting mechanism, a distributed MPC scheme is proposed, and the feasibility and stability conditions are established. In the third step, the robust distributed MPC problem for large-scale nonlinear systems subject to control input constraints, communication delays and external disturbances are studied. A dual-mode robust distributed MPC strategy is designed to deal with the communication delays and the external disturbances simultaneously, and the feasibility and the stability conditions are developed, accordingly.en_US
dc.description.proquestcode0548en_US
dc.description.proquestcode0544en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.bibliographicCitationH. Li and Y. Shi, Network-based predictive control for constrained nonlinear systems with two-channel packet dropouts, IEEE Transactions on Industrial Electronics, accepted Apr. 2013.en_US
dc.identifier.bibliographicCitationH. Li and Y. Shi, Robust output feedback model predictive control for constrained linear systems with intermittent measurement, Systems & Control Letters, vol. 62, no. 4, pp. 345-354, 2013en_US
dc.identifier.bibliographicCitationH. Li and Y. Shi, Robust H_infty filtering for nonlinear stochastic systems with uncertainties and Markov delays, Automatica, vol. 48, no. 1, pp. 159-166, 2011.en_US
dc.identifier.bibliographicCitationH. Li and Y. Shi, Networked min-max model predictive control of constrained nonlinear systems with delays and packet dropouts, International Journal of Control, DOI:10.1080/00207179.2012.751628, pp. 610-624, 2012.en_US
dc.identifier.bibliographicCitationH. Li and Y. Shi, Robust distributed model predictive control of constrained continuous-time nonlinear systems, sumitted, 2012.en_US
dc.identifier.bibliographicCitationH. Li and Y. Shi, Distributed model predictive control of constrained continuous-time nonlinear systems with communication delays, submitted, 2012.en_US
dc.identifier.bibliographicCitationH. Li and Y. Shi, Robust distributed receding horizon control of continuous-time nonlinear systems: Handling communication delays and disturbances, submitted, 2012.en_US
dc.identifier.urihttp://hdl.handle.net/1828/4566
dc.languageEnglisheng
dc.language.isoenen_US
dc.rights.tempAvailable to the World Wide Weben_US
dc.subjectControl systemen_US
dc.subjectNetworked control systemen_US
dc.subjectModel predictive controlen_US
dc.subjectcommunicaiton constraintsen_US
dc.subjectRobust filteringen_US
dc.subjectDistributed model predictive controlen_US
dc.subjectRobust controlen_US
dc.subjectNonlinear systemen_US
dc.titleFiltering and Model Predictive Control of Networked Nonlinear Systemsen_US
dc.typeThesisen_US

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