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Improved sliding mode control for mobile manipulators based on an adaptive neural network
Zhengnan Li,Lidong Ma,Zhijuan Meng,Jin Zhang,Yufeng Yin 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.5
In this study, a wheeled mobile manipulator was modeled while considering the case of wheel-ground slippage. Considering the whole system, the number of states in the dynamic system equation was reduced by the kinematic solution, which facilitates the control of the system. For the system state equation, the improved sliding mode control method was applied, a flush continuous control term and a super-twisting algorithm were used to achieve the improved sliding mode control, and the gain of the super-twisting algorithm was adaptively controlled. The modeling error in the subsystem and the uncertain slippage were approximated by a neural network. The middle layer weights of the neural network were updated by the adaptive control law, and the stability of the system was demonstrated by a quadratic Lyapunov function. The simulation results show the superiority of the control method proposed in this paper by comparing them with results for the traditional sliding-mode control method and the improved sliding-mode control method.
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