Adaptive control on manifolds with RBF neural networks

We propose a new method of adaptive control on manifolds for nonlinear plants in the full-state feedback case using radial basis function (RBF) neural networks. We introduce a procedure for synthesis of adaptation algorithms based on associated performance criteria. We analyze applicability of the algorithms developed for a quadratic performance criterion