Fractional-Order Model Predictive Controller for Process Plant's Robust Performance

Recent research has explored fractional order model predictive control (FOMPC) in various control systems, including power energy, thermal, medical instrumentation, and movement control. Thus, this study focuses on developing a FOMPC model for process plants and comparing its robust performance with linear Model Predictive Control (MPC). The objective is to evaluate the effectiveness of FOMPC in handling multiple set points and disturbances and implement it in process plants. MATLAB/SIMULINK software simulates the process plant performance, derives the targeted transfer function, and implements FOMPC using Oustaloup's approximation. The comparison between MPC and FOMPC will involve performance measures, including rise time, settling time, overshoot, and steady-state.