Research On Intelligent Predictive Control And Its Applications

Intelligent predictive control has started to present as one of the new research domain of model predictive control. The studies and applications of intelligent predictive is discussed in this dissertation. Several new control strategies are present in this paper. In this paper, a kind of intelligent predictive control algorithm is designed and applied in Hangzhou cement plant. In conclusion the main contents are as follows:1. Based on the introduction of the principles of Takagi-Sugeno(T-S) fuzzy model and generalized predictive control(GPC) algorithm, the fuzzy predictive control method combining GPC and T-S model is classified as three kinds of algorithms. The design method of these algorithms is presented in detail. A comparison of these FGPC strategies in control performance and complexity of computation is given by simulation.2. The cement rotary kiln is a complex process, which has nonlinear and time-varying characteristic and exist strong and frequent disturbance, so global model is hard to establish. Based on analysis of the characteristics of the decomposing furnace in Hangzhou cement rotary kiln plant, a new fuzzy predictive control method with multi-model structure is proposed. The parameters of T-S fuzzy model can be modified, depending on the flow of raw material. Real time control software of this algorithm has been developed on the platform of Plantscape distributed control system of Honeywell Corporation. Application results exhibit the superiority of the proposed method over conventional ones even on the condition of existing large delay and time-varying parameters. It has improved the decomposing rate of cement from 81.5% to 89.1%, ensured the temperature varying within ?0% 癈.3.Grey prediction is a kind of effective prediction method, which only needs few output sample data (four data are enough) for modeling a system. Therefore, it is easy to model a system without complex computations. Based on the introduction of grey system modeling theory, a kind of fuzzy predictive controller using grey model isinproposed. A fuzzy decision making mechanism of the grey model 's prediction step is applied to improve the performance of fuzzy controller. Simulation results show the superiority of the proposed method over the conventional fuzzy controller and the grey model predictive fuzzy controller with fix predictive step size.4. Neural net predictive control is an important branch of the intelligent predictive method. By considering the nonlinear characteristic of PH neutralization process, a nonlinear DMC control scheme, based on the CM AC model which is used to model the titration equation, is proposed to overcome the nonlinear disturbance caused by the unknown spices existing in the process stream. The effectiveness of this strategy has been verified via simulation.5. The conflict between convergent speed and solution accuracy has been the impediment when GA is applied in nonlinear predictive control. In order to overcome this problem, a heuristic generic algorithm (HGA) is proposed in nonlinear predictive controller based on CMAC predictive model. The main characteristics of HGA are that it can change search space online according to the process state while performing the online optimization. So it can enhance the convergent speed and solution accuracy simultaneously. Simulation results demonstrate the feasibility of the proposed algorithm.