A new adaptive control algorithm for systems with multilinear parametrization

Adaptive control of nonlinearly parametrized (NLP) systems is an unknown field, where few results have been proposed up to now. In this paper, we propose a new adaptive control algorithm for systems with multilinear parametrization, that belong to the class of nonlinear parametrizations. The proposed controller is a non certainty equivalence one where only the original parameters, without then the need of over parametrization, are adapted. An important feature of the proposed approach is that its convergence properties are not based on projections inside the hypercube to where the parameters are known to lie. Simulations show the efficacy of the approach highlighting this fact, that is, that convergence holds even for the case where the adapted parameters do not belong to the hypercube where the true parameters are known to be