Improved Glowworm Swarm Optimized Algorithm And Its Application In Robust Control Combustion System

In thermal power plants, coal consumption is very large, the boiler combustion system is also an important part of the plant, so the boiler combustion control system directly reflects the quality of China’s coal energy whether it can be used efficiently. Power plant boiler combustion system has characteristics of strong coupling, nonlinear, large inertia, time-varying parameters,etc. Creating a mathematical model of its implementation is very difficult to accurately control.Since the boiler inherent delay characteristics of the traditional heat and temperature signals can not react quickly and accurately within the combustion chamber, resulting that control effect is not ideal. The subject main design H∞ robust controller for boiler fuel control system. For the choice of weighting function of robust controller problem, improved glowworm swarm optimized algorithm has been proposed. Finally, the improved glowworm swarm optimized algorithm is used for optimizing robust weighting function.In order to improve the combustion system signal transmission speed, the subject will be referenced to the radiant energy signal cascade combustion control system as a H∞ robust controller feedback signal. The optimal approximation model has been got by an order approximation varying delay, and H∞ robust controller has been designed by designing the weighting function. And the robust stability and anti-jamming capability of H∞ robust controller has been analyzed.In the design of H∞ controller, the choice of the weighting function is of vital importance.Traditional weighting function selection is mainly got through trial and error, and the quality of the selected weighting function to a large extent depends on the designer’s experience. It is very difficult to get the optimal weight function. The weighting function selection can be converted into a substantially complex multidimensional function optimization, and for this problem the improved glowworm swarm optimized algorithm has been proposed based on glowworm swarm optimized algorithm, artificial fish algorithm and genetic algorithm. In this paper, the improved glowworm swarm optimized algorithm is used for selecting the best weighting function.Simulation results show that robust control system optimized by the improved glowworm swarm optimized algorithm has good dynamic performance and robustness.