Fractional Integral Sliding Mode Control for Trajectory Tracking of Baxter Robot Manipulators
A fractional integral sliding mode control algorithm is proposed to solve the problems of poor tracking accuracy and poor robustness for multi-degree-of-freedom manipulators during trajectory tracking. This method combines the advantages of sliding mode c
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Abstract. A fractional integral sliding mode control algorithm is proposed to solve the problems of poor tracking accuracy and poor robustness for multi-degree-of-freedom manipulators during trajectory tracking. This method combines the advantages of sliding mode control strategy with fractional integration, using exponential reaching law based on fractional integral sliding mode surface. In addition, the approximate estimation term of external disturbance is added to the system, which can achieve rapid convergence and has strong anti-interference ability. Moreover, the stability of the system could be guaranteed by the Lyapunov theory. Numerical simulations of the seven degree-of-freedom(7DOF) Baxter robot manipulators shows promising results that validate the high-precision tracking performance and the better robustness of the proposed robot system with external disturbances. Keywords: Multi-degree-of-freedom manipulator · Trajectory tracking · Sliding mode control · Exponential reaching law
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Introduction
Multi-degree-of-freedom manipulators are widely used in important links of industrial production due to their high speed, dexterity, and precise repeatability. It is a nonlinear and strongly coupled time-varying system [1,2], because of its limited tasks and joint space. There are a series of uncertain factors such as system modeling errors, joint friction, and unstable signal detection etc. The dynamic performance of the system is difficult to express with an accurate mathematical model. Therefore, the control of multi-degree-of-freedom manipulators has become a research hotspot of scholars at home and abroad in recent years [3,4]. In view of the trajectory tracking problem of the robotic manipulators, there are many control methods proposed at present, including adaptive control [5], c The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Y. Jia et al. (Eds.): CISC 2020, LNEE 706, pp. 809–817, 2021. https://doi.org/10.1007/978-981-15-8458-9_86
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X. Wu and J. Jia
PID control [6], sliding mode control [7], fuzzy theory and neural network control [8], etc. Sliding mode variable structure control makes the state of the system slide along the sliding mode surface by switching the control amount. The invariant characteristics of the system can reduce the influence of parameter perturbation and external interference, so it is widely used in robot control. Tairen Sun et al. [9] designed a sliding mode adaptive control based on neural network, which combines sliding mode technology and adaptive technology to ensure trajectory tracking of the robotic manipulators. Qiao Lei et al. [10] designed an adaptive second-order fast non-singular terminal sliding mode control scheme, which is used to track the trajectory of a fully driven autonomous underwater vehicle in the presence of dynamic uncertainty and time-varying external interference. Amir Salimi Lafmejani et al. [11] studied the trajectory tracking control of a 6-DOF pneumatic Gough-Stewart parallel
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