Predictive Control based on Equivalent Dynamic Linearization Model

TL;DR

This paper introduces a model predictive control approach based on an equivalent dynamic linearization model (EDLM) for SISO and MIMO systems, effectively addressing disturbance rejection and providing clearer stability analysis.

Contribution

It proposes a disturbance-compensated MPC based on EDLM for nonlinear and linear systems, enhancing understanding of system stability and practical controller design.

Findings

Improved disturbance rejection in control systems.

Clearer system stability analysis compared to existing methods.

Enhanced practical applicability for engineers.

Abstract

Based on equivalent-dynamic-linearization model (EDLM), we propose a kind of model predictive control (MPC) for single-input and single-output (SISO) nonlinear or linear systems. After compensating the EDLM with disturbance for multiple-input and multiple-output nonlinear or linear systems, the MPC compensated with disturbance is proposed to address the disturbance rejection problem. The system performance analysis results are much clear compared with the system stability analyses on MPC in current works. And this may help the engineers understand how to design, analyze and apply the controller in practical.