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Abstract
In the actual operation site, the dynamics of robotic manipulators is affected by two uncertainties, i.e., external disturbances and modeling errors. In this paper, an adaptive fuzzy backstepping controller based on dynamic surface control is proposed to track and control the robotic manipulator while considering both uncertainties and also making a distinction. Firstly, a feedback control technique is used to convert the robotic manipulator dynamics model into two first-order systems, and the control inputs to be designed are introduced. Secondly, the uncertain modeling errors are approximated using two fuzzy networks, and the external disturbances are assumed to be less than some upper limit. Thirdly, in order to weaken the traditional problem of “explosion of complexity” in the design of the adaptive backstepping controller, a dynamic surface control technique is used in this paper. Then, the stability of the designed controller is demonstrated using Lyapunov theory. Finally, simulations are performed with a two-linked robotic manipulator to show the effectiveness of the designed controller, and then, to show the superiority of the controller, simulation results are compared with the results obtained by other control algorithms.
Highlights
The robotic manipulator, as a typical dynamics system, has been commonly used in industrial fields
A finite time adaptive backstepping fault tolerant controller based on fractional-order theory is proposed in [9] for robotic manipulators in the presence of uncertainties, unknown external load disturbances and actuator faults to achieve fast response and high-precision tracking performance. [10] investigates a new controller based on the combination of sliding mode control and backstepping control strategy for the tracking control problem of the uncertain welding robot
Motivateded by the successful application of DSC techniques in engineering fields, this paper proposes an adaptive fuzzy backstepping dynamic surface control (AFBDSC) for uncertain robotic manipulators to improve control performances
Summary
The robotic manipulator, as a typical dynamics system, has been commonly used in industrial fields. Dandan Lei and his co-authors successfully developed composite controllers based on DSC technique for micro-gyroscope [20,21] to improve the timeliness and effectiveness of tracking and other performances in the presence of model uncertainties and external disturbances. Motivateded by the successful application of DSC techniques in engineering fields, this paper proposes an adaptive fuzzy backstepping dynamic surface control (AFBDSC) for uncertain robotic manipulators to improve control performances. The DSC is integrated into the adaptive fuzzy control scheme by using the backstepping design framework, where two fuzzy networks are used to estimate the modeling error in order to reduce the number of fuzzy rules, and the DSC technique is used to overcome the general phenomenon of “explosion of complexity” inherent in the backstepping design method.
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