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The majorities of the existing predictors for states are model-dependent and therefore require some prior knowledge for the identification of complex systems, usually involving system identification, extensive training or online adaptation in the case of time-varying systems. In this paper a model-free predictor (MFP) for a time series produced by an unknown nonlinear system or process is proposed...
The on-line optimal control of operation is difficult to achieve with routine optimization methods because of the nonlinear thermal system and the changing frequently conditions in start-up, stop and load change of the large-scale thermal power plant. Based on the research of three typical evolution optimization methods which are evolution strategies, genetic algorithm and evolution programming in...
This paper addresses the robust fuzzy control problem for nonlinear multiple time-delay large-scale systems in the presence of modeling errors and the state variables unavailable for measurement. The Takagi-Sugeno (T-S) fuzzy control system with modeling errors is adopted for modeling the nonlinear multiple time-delay large-scale systems and establishing fuzzy state observer. In terms of Lyapunovpsilas...
This paper proposes an approach to control design of biological wastewater treatment (WWT) plants based on rigorous treatment of the complex mathematical models from a nonlinear control theoretical viewpoint. Without resorting to order reduction, localization and linearization of process models, this paper provides a promising avenue to model-based control design for necessary innovations of modern...
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