Study of two-cell immune feedback control for water level of boiler drum based on gray prediction
Due to the ‘false water level’ phenomenon in power station makes the traditional control strategy can't be a good solution to the problem, a two-cell immune feedback control strategy based on gray prediction for water level of boiler drum in power station is proposed, which using the function of gray prediction with strong self-adaptability and advanced control functions, and learning from bio-feedback mechanism of the immune system and regulating rule of response process. Through lots of simulation studies, it can achieve a more satisfied control quality with strong robustness and anti-jamming capability. Meanwhile, the structure and algorithm of the control strategy are simple and easy to engineering implementation.
Immune PID Cascade Control of Fresh Steam Temperature Control System in Fossil-fired Power Plant
Since fresh steam temperature control systems of fossil power plants are characterized by large inertia, long time lag and variation with time, satisfying control effect can not be achieved with traditional control methods of fresh steam temperature systems which use the normal PID cascade control methods. Biology immune systems are characterized by their strong robustness and self-adaptability even when encountering strong disturbances and uncertain conditions. Prompted by the regulation law of immunity feedback response in biology, immune PID cascade control is being suggested for controlling fresh steam temperature in fossil-fired power plants. Simulation studies of high temperature superheaters under 4 typical operating conditions of a certain supercritical 600 MW power boiler show that the control effect by this strategy is superior to that of normal PID cascade control. It is featured by strong robustness and self-adaptability, and can readily accommodate itself to the object's parameter variations. Figs 5, tables 2 and refs 8.
Tuning of a PID controller using immune network model and fuzzy set
This paper suggests that the immune network algorithm based on fuzzy sets can effectively be used in tuning of a PID controller for multivariable processes or nonlinear processes. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. The result of study shows the artificial immune network based on fuzzy set can effectively be used to tune the nonlinear process or the multivariable process, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods, against the noise or disturbance, various inputs, and coupling action between loops.