Data-driven observer-based model-free adaptive discrete-time terminal sliding mode control of rigid robot manipulators

Abstract

This paper aims to design a data-driven observer-based model-free adaptive terminal sliding mode controller for rigid robot manipulators whose models are unknown in advance. First, the nonlinear robot manipulator dynamics are transformed to an equivalent linear discrete-time data-model using full-form dynamic linearization technique and multi-observers along with an adaptation law are designed in order to estimate system outputs and pseudo-partitioned Jacobian matrix, respectively. Second, based on a nonlinear data-driven terminal sliding surface, the robust discrete-time controller is obtained. Mathematical analysis guarantees the finite-time convergence and the stability of the closed-loop system. The comparative simulations lighten the superiority of the proposed work and the robustness of the proposed controller against external disturbances is validated by means of simulations.