【摘 要】
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This paper presents a multivariable fuzzy adaptive predictive functional control(MFAPFC)algorithm based on Takagi-Sugeno(T-S)model for multi-input multi-output(MIMO)system.Firstly,the structure parame
【机 构】
：
School of Information and Control Engineering,Liaoning Shihua University,Fushun 113001,PR China
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This paper presents a multivariable fuzzy adaptive predictive functional control(MFAPFC)algorithm based on Takagi-Sugeno(T-S)model for multi-input multi-output(MIMO)system.Firstly,the structure parameters of T-S fuzzy model are confirmed,and the model consequent parameters are identified online using the recursive weighting least square method in order to obtain the precise predictive model and offset for the effect on system performance under model mismatch.Secondly,the nonlinear system is linearized by the identified T-S models and then transformed into time-varying state space model.Finally,the linear predictive functional control is adopted to compute the control law,in which the predictive output error between process output and model predictive output is optimized by improved error compensation,a novel adjusting factor in the performance index is introduced to improve the robustness of system and the future control variable is expressed by the step method.Application results on the pass temperature balance of the ethylene cracking furnace show the proposed control strategy is of strong tracking ability and robustness.
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