Steam Temperature System, Neural Network Control Method

The super-heated steam temperature is the maximal temperature in the whole steam channels at the process of thermodynamic engineering in power plant. If the steam temperature is too high or too low, it will bring on dangerous factors. We must control the super-heated steam temperature of the output of the super-heated implement to an expected range. The vapor object is a multi-container tache. It has pure lag and many disturbances. Its constant time is much bigger and its object model is not confirmable. It is the most difficult control system in the process of thermodynamic engineering. The traditional control method such as PID controller is implemented widely in the process of thermodynamic engineering now. But they work well only when the systemic load is steadily and can not work well when the systemic load is changed with a wide margin. With studying of the intelligent control theory, it provides a new control method for the process of thermodynamic engineering in power plant.At first, the author analyzes many disturbance factors in vapor temperature on the basis of the produce technics in power plant. The vapor object has complicated dynamic process and intricate object model. It has many disturbances. Such as vapor flux, burning medium, water temperature, vapor temperature entrance into the super-heated implements. These factors may affect on each other. On the basis of analyzing the three main disturbance factors in vapor temperature and the main dynamical characteristic of the super-heated steam temperature control system in power plant, this paper builds the vapor temperature math model for simulation by use of mechanism analyzing.Based on the single neuron control theory, this paper analyzes the neuron plus influence on control performance on the foundation of the basic neuron control algorithm. Simulation results prove that for the control objects which have a more large opened-loop plus, it can weaken the control effect of the neural controller and abate the system responseoverall plus and oscillation, for the control objects which have a less smaller opened-loop plus, it can strengthen the control effect of the neural controller and quicken the system response. These request the neuron plus to have self-adjusting ability. If we can apply the regular PID algorithm and the error between practice output and expected output and its radio of its changing to decide the neural controller plus, we can design a self-adjusting plus single neural controller based on regular PID algorithm. At the same time, we also provide neuron control algorithm about the performance target based on the output error square function. The paper designs the control project about the super-heated steam system. To overcome the disturbance factors, we apply series control system to the steam system. The main controller adopts the self-adjusting plus single neural controller and the minor controller adopts the conventional PI controller. As compared with the neural controller and the conventional PID controller is simulated. The experiment shows that the effect of the neural controller is better and it is superior to the conventional controller on the condition of joining the inner loop vapor flux disturbance and outer loop smoke temperature disturbance and other conditions.Aimed at the problem the self-adjusting plus single neural controller based on regular PID algorithm has a slow response velocity, the author analyzed two improved algorithm of the neural controller. One is separate integral neural controller, another is attenuation function neural controller. The author analyzed some parameter influence on control performance and defined the attenuation function and its algorithm. The simulation comparisons between two neural intelligent controllers show that the attenuation function neural controller is superior to the self-adjusting plus single neural controller in response velocity, and its algorithm is simple and easy. Then, aimed at the basic neuron control algorithm, simulation experiments were made. The auth...