Stable auto-tuning of the adaptation gain for indirect adaptive control
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abstract
Indirect adaptive control is a widely known control scheme in which we approximate parts of the plant dynamics that are used by a feedback controller to cancel the system nonlinearities. 'Approximators' such as linear mapping, 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 used for a class of nonlinear discrete-time systems.
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Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334)