Hybrid Fuzzy Convolution Modelling and Identification of Chemical Process Systems
نویسندگان
چکیده
This paper looks at a new method of modelling non-l inear dynamic processes, using grid-type Sugeno fuzzy models and a priori knowledge. The proposed hybrid fuzzy convolution dynamic model consists of a non-linear fuzzy steady-state static, and a gain-independent impulse response model-based dynamic part. The modelling of non-linear pH processes is chosen as a realistic case study for the demonstration of the proposed modelling approach. T he off-line identified hybrid fuzzy convolution model is shown to be capable of modelling the non-linear process and providing better multi-step prediction than the conventional grid-type Sugeno fuzzy model.
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