Stable auto-tuning of the adaptation gain for indirect adaptive control

Indirect adaptive control is a widely known control sdwme iu which we approxima te parts of the plant dynamics that are used by a feedback controller to cancel the the system nonlinearities. "Approximators" such as linear mappings, polynomials, fuzzy systems, or neural networks can be used. Here, we present two algorithms to tune the adaptation gain for a gradient-based approximator parameter update law use for a class of uonlinear discrete-time systems.