Neurofuzzy Power Plant Predictive Control

摘要

In unit steam-boiler generation, a coordinated control strategy is required to ensure a higher rate of load change without violating thermal constraints. The process is characterized by nonlinearity and uncertainty. Using of neuro-fuzzy networks (NFNs) to represent a nonlinear dynamical process is one choice. Two alternative methods of exploiting the NFNs within a generalised predictive control (GPC) framework are described. Coordinated control of steam-boiler generation using the two nonlinear GPC methods show excellent tracking and disturbance rejection results.