Granulator intelligent control using bio-inspired optimization and fuzzy-expert stratagy

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  For a wide class of time-delay and parameter uncertainty systems,it is quite often to see that prediction models are not effective and uncertain information cannot be accurately described.In this paper,with a strong globally searching capability,a novel optimization strategy based on a bacterial foraging algorithm(BFA)is proposed,which can achieve dynamic optimization of systematic parameters and overcome the problem of inefficiency in selecting optimal parameters.Meanwhile a novel intelligence control strategy based on fuzzyexpert method is designed.Comparing with classical algorithms,the proposed method has better control tracking effect than PID and Fuzzy control.The DCS experiments show that our approach can be used to control the temperature to+/-1.3% up from+/-5% of technic error.
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