Exponential Tracking Control Using Backstepping Approach for Voltage-Based Control of a Flexible Joint Electrically Driven Robot

This paper addresses the design of exponential tracking control using backstepping approach for voltage-based control of a flexible joint electrically driven robot (EFJR), to cope with the difficulty introduced by the cascade structure in EFJR dynamic model, to deal with flexibility in joints, and to ensure fast tracking performance. Backstepping approach is used to ensure global asymptotic stability and its common algorithm is modified such that the link position and velocity errors converge to zero exponentially fast. In contrast with the other backstepping controller for electrically driven flexible joint robot manipulators control problem, the proposed controller is robust with respect to stiffness uncertainty and allows tracking fast motions. Simulation results are presented for both single link flexible joint electrically driven manipulator and 2-DOF flexible joint electrically driven robot manipulator. These simulations show very satisfactory tracking performances and the superiority of the proposed controller to those performed in the literature using simple backstepping methodology.

Simulation of a hybrid adaptive-learning control law for a rigid link electrically driven robot manipulator

In this work, a hybrid adaptive/learning controller is simulated in Simulink using a two-link robot manipulator for a sinusoidal desired position. The two-dimensional nature of control law makes direct simulation difficult. Simulation results demonstrate that the controller achieves semi global asymptotic position tracking.