Human Simulated Intelligent Control In The Condensation Reaction

Interim Reactor is a fine chemical widely used in bio-chemical process equipment, its operation has a strong non-Linearity, log and so on. General conventional control is difficult to achieve the desired control requirements, and this paper presents a combined neural network. Network and genetic algorithm based on artificial neural network internal model control method.The basic idea of Human Simulated Intelligent Control is that the behavior of the human nervous system function of simulation, after years of development, now has accumulated a wealth of theoretical knowledge, and through attempts to establish model is applied to a variety of industries, has achieved initial results. Humanoid intelligent control is characterized by multi-modal control, which combination of the open-closed-loop control.Neural network has the ideal for any non-linear mapping approximation ability, and can learn and adapt to uncertain systems with unknown dynamics, so that neural network control system has a stronger adaptability and robustness. This neural network and the combination of humanoid intelligent control is proposed based on neural networks for humanoid intelligent control methods. The method uses neural networks ideal for any non-linear mapping approximation ability, timely changes in control parameters, to achieve control purposes.This article internal model control method is applied to the process of condensation reaction temperature, pressure control, the simulation results and the actual operation proves that the method is better to complex condensation reactor control of temperature and pressure.