Observer-Based Robust Adaptive Control of Uncertain Robot Manipulator

Programmable, multifunctional manipulators have become mandatory in the traditional light and heavy industries and in medicine, space exploration, deep-water energy exploration, and operational or recovery missions in hostile environments. Trajectory planning of the robotic manipulator is significant to any of these applications. The manipulator's performance in this endeavour is influenced by parametric, non-parametric uncertainties, unmodeled dynamics and external disturbances. Ultimately, in addition to not verifying the required specifications, such uncertainties will result in the reduced life span of the manipulator. Several possible control strategies have been proposed in the literature. This paper presents an observer-based robust adaptive control strategy with both time-invariant and time-varying observer gains. The objective is to minimize the undesirable disturbances and make the system follow a chosen reference model dynamics or trajectory. Simulation results show that the proposed robust adaptive control scheme achieves boundedness for all the closed-loop signals and ensures convergence of the tracking error.