Design of LQR and LQG Control Systems for the RIG 38-100 Process

Abstract

This paper presents the design of a control system to regulate water levels and flow rates, ensuring that the water level remains at a normal setpoint despite variations in load or input conditions. This approach aims to enhance the safety and efficiency of water level management. Nonlinear behaviors in the system are addressed during level regulation, but for analytical simplicity, the system is typically assumed to be linear in foundational studies. In this research, the nonlinear system is linearized to facilitate modeling in a state-space representation. The proposed control strategy employs the Linear Quadratic Gaussian (LQG) optimal control method, which integrates the Linear Quadratic Regulator (LQR) technique with the Kalman Filter. The LQR component is designed to optimize the system states, while the Kalman Filter provides noise-free estimations of water level and flow rate. The controller's implementation and performance evaluation were conducted using MATLAB/Simulink software. The study compares the plant's dynamic response under loaded and unloaded conditions, demonstrating the effectiveness of the proposed method in achieving stable and efficient control.