Accelerating Adaptive Systems via Normalized Parameter Estimation Laws
This research introduces normalized parameter estimation laws to speed up adaptive systems' convergence by promoting signal sparsity over time. Instead of standard methods, these new laws guarantee that a specific power of the state norm is integrable, which forces the system state to decay faster. This acceleration works without needing persistent excitation or prior knowledge of parameters.