The Application Of Thermal Power Plant Main Steam Temperature Control System Based On Improved Particle Swarm Optimization

In modern thermal power plant,stability of main steam temperature is very important to security and economy of unit operation.Therefore, It is very strict to the control of main steam temperamre , and it is important to get a reasonable and effective control in the themal power plant. PID controller is still the most primary control strategy in the control of main steam temperamre of power plant. But main steam temperature is a complex object with the features of large inertia, large delays,non-linear and varity time, it has some shortcomings to control the main stream by using conventional PID controller. Particle Swarm Optimization(PSO)is a kind of group intelligent heuristic evolutional algorithm, it transfers the process of seeking the best solution for specific problems to the process which particles scout the best position in a certain area by simulating the foraging behavior of birds. So this thesis uses PSO to optimize PID controller's parameters of the control of main steam temperamre.This thesis first introduces the principles of PID controller, parameter tuning methods and control system performance evaluation; then introduces PSO algorithm principle and the mainly involved method improving the PSO algorithm. PSO has some defects such as following:premature convergence, slow convergence rate in the optimization process later, and easlly turning into local optimization. In response to these defects, this thesis introduces Quantum behaved Particle Swam Optimization and the mechanism of mutating which mutating the individuals in adaptive mutating probability, thus puts forward a type of improved PSO algorithm. In order to verify the performance, four standards test functions are used to test the improved algorithm, the experimental results show that the improved algorithm has better convergent speed and accuracy; and then the improved PSO is applied in PID controller parameters tuning process, and the experimental results show that this parameters optimization algorithm has fine control effect; Finally, the improved PSO is applied in the cascad control of main steam temperamre, and the simulation results show that the main steam temperature control system based on improved particle spwarm optimization has better control performance and robustness.