System Identification and Adaptive Control

This article explores MATLAB simulations for system identification and adaptive control. We will examine the fundamental concepts and principles of system identification, demonstrating how to implement these techniques in MATLAB using functions such as tfest for transfer function estimation and pem for prediction error minimization. The discussion extends to adaptive control concepts and applications, providing practical MATLAB simulation examples that illustrate implementation approaches like recursive least-squares algorithms and model reference adaptive control (MRAC) using adapt functions and Simulink blocks. We will analyze the relationship between system identification and adaptive control, showing how their integration—such as using online parameter estimation with recursiveARX—enhances control system efficiency. Readers will gain comprehensive insights into both domains and foundational knowledge for implementing these concepts in MATLAB through code-driven examples and algorithm explanations.