Stable auto-tuning of the adaptation gain for direct adaptive control
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Direct adaptive control is a widely known control scheme in which the controller attempts to approximate the ideal controller directly. '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 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)