Programming Example for Adaptive Generalized Model Predictive Control

This programming example for adaptive generalized model predictive control demonstrates the implementation process to help develop a deeper understanding of this control methodology. The example covers fundamental concepts and sequential steps including model construction techniques using state-space representation, predictive control implementation through optimization algorithms, and adaptive model adjustment mechanisms employing recursive parameter estimation. We will elaborate on specific operations and technical aspects at each stage, such as cost function formulation, constraint handling, and real-time parameter updates using recursive least squares (RLS) methods. The implementation showcases key MATLAB functions like fmincon for optimization and practical approaches for system identification. Through this comprehensive example, you will gain enhanced insight into applying adaptive generalized model predictive control to practical industrial production and control processes with improved implementation strategies.