Fuzzy economic model predictive control for thermal power plant

In a modern thermal power plant, fuzzy model predictive control (MPC) is an effective method for realising load tracking and economy of boiler–turbine system, by using fuzzy modelling technique considering the plant thermal dynamic. The power plant economy is generally handled in a hierarchical MPC (HMPC) architecture, in which the upper layer realises the economic optimisation while the low layer realises the dynamic tracking. However, while this HMPC architecture realises the steady-state optimisation, it may neglect the dynamic optimum of the total power plant process. This study develops a fuzzy economic MPC to utilise the economic index directly as the cost function. It integrates economic optimisation and dynamic tracking of the boiler–turbine system control into one framework. Since a fuzzy model is used to approximate the system's non-linear behaviour, a linear feedback controller can be constituted for guaranteeing the feasibility and stability of the boiler–turbine system through linear matrix inequality. Simulation results are given to show the effectiveness of the proposed controller.