A Numerical Investigation of Indirect Adaptive Predictive Control with Structure-Informed Nonlinear Regressors
The research developed Adaptive Predictive Control using structure-informed nonlinear regressors for online operation on streaming data. The method uses kernel-based identification and a closed-form solution via Cholesky factorization to compute control sequences directly, avoiding complex iterative optimization. This allows the controller to adapt online to system changes while maintaining high accuracy.