Nonlinear Controller Synthesis for a SISO Steam Boiler System Application

Abstract

This paper aims to develop a nonlinear control algorithm to optimize the operation of a single input single output (SISO) steam boiler system. First, a dynamic model based on mean density and mean specific internal energy is developed and validated against published data to accurately capture the system's behavior. Building on this model, two advanced nonlinear control strategies—Generic Model Control (GMC) and Globally Linearizing Control (GLC)—are systematically designed to improve system performance. To address the challenge of unmeasurable internal states, a Lyapunov-based state observer is formulated and integrated with the nonlinear controllers. For comparison, a conventional Proportional-Integral (PI) controller is also implemented. Simulation results demonstrate that the observer-enhanced GMC approach significantly outperforms both GLC and PI controllers in regulating boiler steam temperature through heat input manipulation. The work offers a novel integration of nonlinear control, state estimation, and performance benchmarking, contributing a robust and realistic solution to the control of nonlinear energy systems.