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Model Reduction Method and Optimized Smith Predictor Controller Design using Reduced Model  

최정내 (원광대 공대 전기공학과)
조준호 (원광대 공대 제어계측공학과)
이원혁 (원광대 공대 제어계측공학과)
황형수 (원광대 공대 전기전자및정보공학부)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers D / v.52, no.11, 2003 , pp. 619-625 More about this Journal
Abstract
We proposed an optimum PID controller design method of the Smith Predictor It can be applied to various processes. The real process is approximated via the second order plus time delay model (SOPTD) whose parameters are specified through a model reduction algorithm. We already proposed a new model reduction method that considered four point in the Nyquist curve to reduced the steady state error between the real process model and the reduced model using the gradient decent method and the genetic algorithms. In addition, the Smith predictor is used to compensate time delay of the real process model. In this paper, the new optimum parameter tuning algorithm for PID controller of the Smith Predictor is proposed through ITAE as performance index. The Simulation results show the validity and improvement of performance for various processes.
Keywords
Model reduction; Genetic algorithm; Smith Predictor;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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