Reaserch Of Fuzzy Generalized Predictive Control Algorithms In Nonlinear System

Predictive control is a class of digital control algorithms developed in the late of 1970's. The popularity of these methods is due to the facts that they can offer good performance, be understood and formulated easily and accommodate input/output process constraints. Because of robustness to the model uncertainty, predictive control strategies have received much attention in the literatures and been applied in industries widely. By far, the theory of linear SISO predictive control has matured considerably. Unfortunately, MIMO and/or nonlinear systems are frequently encountered in most applications. It is necessary to improve control algorithm more adaptive to complex industrial processes. With the combine between the fuzzy control theory and predictive control mechanism, as the fuzzy predictive control, is the new direction of the developing of the predictive control. The fuzzy predictive control algorithm is applied in the PH neutralization control in this paper. In conclusion the main contents are as follows:1 Review the developing of fuzzy control and the predictive control. And tell of the necessary of combine the two algorithms as a new algorithm named fuzzy predictive control.2. The method of T-S model identification is proposed. For the black-box system, there is two step to identification the T-S model, first, apply the GK cluster algorithms and LS algorithms to identification the initialization T-S model, second, apply the fuzzy neural network to further optimal the T-S model. For the grey-box system, also there is two step to identification the T-S model ,first, apply the ant colony algorithms to identification the initialization T-S model, second, apply the fuzzy neural network to further optimal the T-S model.3. Present the method of transform the T-S model into CARIMA model, and apply the GPC algorithms into the nonlinear process control.4. Compare the fuzzy predictive control with the traditional PID control in the control of PH neutralization process of the strength nonlinear system, and validate the robustness of the fuzzy predictive control algorithms.