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Zhang G.,Control and Simulation Center | Han C.,Space Control and Inertial Technology Research Center | Guan Y.,Harbin Institute of Technology | Wu L.,Space Control and Inertial Technology Research Center
International Journal of Innovative Computing, Information and Control | Year: 2012

This note considers the problems of stability and stabilization for discretetime switched nonlinear systems with time-varying delay. The nonlinearity is assumed to satisfy a special constraint. The purpose of the robust stability problem is to give conditions such that the discrete-time switched nonlinear delay system is exponentially stable, while the purpose of stabilization is to design a state feedback control law such that the resulting closed-loop system is exponentially stable. By applying the average dwell time approach together with the piecewise Lyapunov function technique, also by constructing a proper Lyapunov-Krasovskii functional and employing the free-weighting matrix method, some delay-dependent stability conditions are proposed. A strict linear matrix inequality (LMI) design approach is developed. An explicit expression for the desired state feedback control law is also given. Finally, two numerical examples are provided to demonstrate the application of the proposed methods. © 2012 ISSN 1349-4198. Source

Yang T.,Harbin Institute of Technology | Yang T.,Space Control and Inertial Technology Research Center | Qiu W.,Harbin Institute of Technology | Ma Y.,Harbin Institute of Technology | And 4 more authors.
Neurocomputing | Year: 2014

The paper is concerned with the design of a fuzzy model-based predictive controller for activated sludge wastewater treatment processes. The control purpose is to maintain the dissolved oxygen concentration in an aerobic reactor of the wastewater treatment plant at the set-point. The fuzzy model of the activated sludge processes is derived based on the Activated Sludge Model No. 1 (ASM1), including the structure of the fuzzy rules. The required fuzzy space of input variables is partitioned by fuzzy c-means cluster algorithm and the consequent parameters are identified using the method of least squares. Compared with both traditional PID control and dynamic matrix control schemes, the proposed fuzzy model-based predictive control paradigm achieves satisfactory benefits in terms of both transient and steady performances. © 2014 Elsevier B.V. Source

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