Efficient Batch and Recursive Least Squares Algorithms for Identifying Matrix Parameters with Applications to Adaptive Model Predictive Control

This work derives efficient batch and recursive least squares algorithms for identifying matrix parameters that minimize the same cost function as the standard vec-permutation approach, while requiring significantly less computational and storage complexity.