Studies on Optimization Control of Networked Systems based on Local Models

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We studied methods to control complex/large/networked systems based on local/uncertain models. We considered the cases where locality of models in space and/or time is assumed and time delays exist in the channels between subsystems. For locality in space and nonlinearity, we proposed an approach using analysis and synthesis techniques of linear parameter varying (LPV) systems ; for locality in time, we proposed a model predictive control approach ; for locality in both space and time, we proposed an approach based on Just-In-Time(JIT) modeling and model predictive control scheme. These approaches are developed through solving two types of control problems for complex/large/networked systems. First, we extended the known method for LPV systems to electro-hydraulic servosystems, which contain nonlinear elements, uncertainties and time delays, and designed a gain scheduled H-infinity controller. Second, we focused our attention to blast furnace which presents very complicated/nonlinear physical phenomena and is difficult to built models, and proposed a new online modeling and predictive control scheme based on a large scale database consisting of blast furnace process data. As for time delays, we conquered this issue by using input/state/output prediction on delay time interval based on models and by transforming the control problems for time delay systems to the ones for LPV systems, which leads to solving some parameter dependent linear matrix inequalities (LMIs). We also discussed a congestion control of nonlinear networks including time delay based on control theory.