Predictive Control And Application Based On Intelligent Computing

With the rapid development of modern industry, industrial system complexity significantly, in view of the complex nonlinear system with time delay, prediction of existing traditional control technology is very difficult to realize the control. In this paper, taking the heating furnace control system as the research object, to seek out a can achieve stability for nonlinear complex system, large time delay, multi disturbance control method, according to the characteristics of the nonlinear system, using predictive control technology based on intelligent computation, realization of control. First of all, with arbitrary approximation and self-learning ability of nonlinear function using neural network, neural network is introduced to identify the nonlinear system, the establishment of prediction model. Secondly, on the basis of random genetic algorithm can search mechanism implemented by means of the characteristics of the search for the global optimal solution of the problem domain, using genetic algorithm to realize the rolling optimization in predictive control. And then, respectively based on the predictive control, neural network, prediction algorithm, this paper assembled into an excellent control scheme. Finally, in the heating furnace fuel gas flow as the control object, the heating furnace outlet temperature as a controlled object, using MATLAB simulation software, good control performance verification based on Computational Intelligence predictive control, finish the study.The goal of this paper is that combine with the neural networks, genetic algorithm, and predictive control, use one to two kinds of method to realize the predictive control of neural network, the neural network as a nonlinear system identification method, and use genetic algorithm to realize the rolling optimization predictive control.