Optimal Regulation of Unknown Nonlinear Systems Based on Locally Weighted Learning

This paper considers the optimal control of unknown nonlinear systems. To deal with the uncertainties in the system, a locally weighted learning observer (LWLO) is proposed. Using the functions approximated within the LWLO, analytic optimal controllers are proposed in the sense of pointwise min-norm. To show effectiveness of the proposed controllers, numerical simulations are presented.