Pressure control of Once-through steam generator using Proximal policy optimization algorithm

Abstract

Due to the strong coupling characteristics of the once-through steam generator(OTSG), the outlet pressure control is difficult. The control system using the Proximal Policy Optimization(PPO) algorithm is designed to control the outlet steam pressure of OTSG. The double-layer controller is designed in two layers, the upper layer is the agent using the PPO algorithm to optimize the parameters of the PID in real-time to obtain better control performance. The bottom layer is the PID controller, which receives the commands from the upper layer to directly regulate the feed water valve of OTSG. In the training process of the controller agent, by adopting deep neural network approximation as the approximator of the critic network and actor-new network, good generalization performance is obtained. Compared with the PID controller, the simulation experiment result shows that the method not only has a good tracking ability but also has a good anti-interference ability.