Convergence Analysis of Nonlinear Model Predictive Control Based on Fractional Hammerstein Model

This study develops a predictive control strategy based on Fractional Hammerstein Models, applicable to both Single-Input Single-Output and Multiple-Input Multiple-Output systems. The proposed predictive control solution is obtained by minimizing a cost function based on the squared prediction error. We have used deterministic optimization methods based on gradient techniques and simplex theory. A convex optimization framework is obtained from the initial non-convex problem by restricting the control space through tightened constraints around the optimal control value that minimizes energy consumption. Indeed, the optimization problem is theoretically studied and the algorithms are analysed and compared in tracking performances.