Nonlinear Adaptive Partial State Feedback Trajectory Tracking Control of Tendon Driven Robot Manipulators

Abstract

In this work, the link position tracking control problem of a tendon driven robotic system is studied in the presence of parametric uncertainty and lack of velocity measurements both of links and actuators. A partial state feedback nonlinear adaptive controller is proposed to deal with the unmeasurable states and uncertain dynamical system parameters. A backstepping approach has been utilized to develop the control strategy. The proposed nonlinear tracking controller utilizes online update laws to adapt for parametric uncertainties, and requires only link and actuator position measurements and tendon tension measurements. Need for link velocity measurements are eliminated by using a nonlinear filter, and a set of linear filters is designed to estimate the actuator velocities. Lyapunov based arguments have been applied to prove the stability of the closed-loop system and semi-global asymptotic link position tracking is achieved.