Fractional-Order Adaptive Backstepping Control of Robotic Manipulators in the Presence of Model Uncertainties and External Disturbances

In this paper, the problem of finite-time stabilization and control of an n-degree of freedom (DOF) robotic manipulator is concerned. Factors such as model nonlinearity, uncertainties, and external disturbances can interfere in a closed-loop system performance. In order to attenuate these effects and improve the response characteristics of the system, a proper controller is developed. This paper is the pioneering one on integrating adaptive backstepping control approach into fractional-order controller design for an integer-order dynamic system. An analytic proof is provided based on the fractional Lyapunov stability theorem to guarantee global asymptotic stability of the controlled system. Ensuring finite-time convergence of the system regardless of initial states values is another important aspect of this study. Furthermore, model uncertainties and external disturbances are taken into account and the controller is developed to attenuate these effects. The developed fractional-order adaptive backstepping controller (FOABC) is experimentally implemented on a manipulator and extensive experiments are carried out. Moreover, an exact comparison between FOABC, integer-order adaptive backstepping controller (ABC), and two of the recently released adaptive control approaches is drawn which gives an evidence of superiority of the controller.