Adaptive model-free control for robotic manipulators

In this paper, a model-free control policy for tracking problem in robotic manipulators with any numbers of degree-of-freedom (DOF) is proposed. Here, it is assumed that the dynamics of manipulators contains bounded unknown nonlinearities and external disturbances. The algorithm includes two separate robust adaptive laws for estimating the unknown nonlinear terms and unknown system matrix. The adaptive law for estimation of the nonlinear terms is a model-free estimation algorithm, since it does not require any regressor parameters. The proposed algorithm is analysed using Lyapunov stability theorem. Moreover, it is shown that the controller incorporates an optimal policy considering a specific cost function. The performance of the proposed algorithm is studied on simulation of a two-arm robotic manipulator with tracking objective.