Adaptive backstepping control for an n-degree of freedom robotic manipulator based on combined state augmentation

The aim of this paper is to improve the tracking performance of a robotic manipulator by designing an adaptive controller and implementing it on the system. The proposed controller guarantees the system stability as well as good tracking performance in existence of nonlinearity and parameter uncertainties. The requirement to decrease the system response overshoot and steady state error as well as increasing speed of tracking for manipulators is essential to many manufacturers. To this mean, in this paper, the tracking error equations for an n-DOF manipulator are derived and the response characteristics are improved by augmenting a new state to the system equations. The stability of the closed-loop system is guaranteed based on the Lyapunov theory via backstepping control approach. The robotic manipulator model contains parametric uncertainties and many of the parameter values are unknown. To solve the problem, an adaption law is proposed via adaptive backstepping mechanism. Different experiments are carried out for a 2-DOF manipulator to show the effectiveness of the proposed approach and the results are compared with four of the recently revealed researches on control. Experimental results present the superiority of the state augmented adaptive backstepping in tracking the desired joint angles. Moreover, in order to present the industrial application of the proposed control method, it is simulated for a large industrial Scara manipulator.