Optimization on Internal Model PID Control for Nuclear Power Pressurizers

Based on the internal model control (IMC) principle and considering that the pressurizer system of nuclear power plant has the properties of large inertia, time-variation and multi-disturbances, an internal model-PID control system was developed. To tune the internal model PID controller parameters, a quantum particle swarm algorithm with high speed convergence was proposed for parameters optimization, of which the effectiveness was verified by classical test functions. Simulation results show that the internal model PID controller has better control effects than conventional PID control systems, and when the attribute of object model changes or the model is disturbed, good control effects can still be obtained by the internal model PID controller, which has higher robustness and anti-interference capability.