Performance Analysis of Linear Robust Model Predictive Control for Small Scale Biomass Combustion Furnace

Abstract

Among the varied sorts of energy sources, biomass is that the finest alternative for a secure and pollution-free source of energy. as compared to big systems, direct biomass combustion for small scale burning furnaces is primarily liable to volatility in heat consumption. Linear model predictive control is a popular process control strategy in recent years. It predicts future control action and trajectories based on present input and output variables and future control signals. LMPC was developed through process control research. MPC uses an internet-based (real-time) optimization problem, a process model, and process data to predict future process behavior. This determines process input values. This study aims to improve the efficiency of a small-scale biomass burning furnace by incorporating a western renewable resource made from agricultural products, industrial byproducts, and household waste.