English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The large inertia and long delay characteristics of main steam temperature control system in thermal power plants will reduce the system control performance. In order to improve the system control performance, a generalized predictive PID control for main steam temperature strategy based on improved particle swarm optimization algorithm is proposed. The performance index of incremental PID controller of main control loop and PD controller of auxiliary control loop based on generalized predictive control algorithm is established. An improved particle swarm optimization algorithm with better fitness and faster convergence speed is proposed for online parameters optimization of performance index. The optimal control value of PID controller and PD controller can be obtained. The simulation experiment compared with fuzzy PID and fuzzy neural network is carried out. Simulation results show that proposed control method has faster response speed, smaller overshoot and control error, better tracking performance, and reduces the lag effect of the control system.

Generalized Predictive PID Control for Main Steam Temperature Based on Improved PSO Algorithm