Neural Control for Image Stabilisation Using a Reference Model
Balbayev G. Mussina A. Zhauyt A. Shingissov B. Kalekeyeva M.
January 2021International Journal of Mechanical Engineering and Robotics Research
International Journal of Mechanical Engineering and Robotics Research
2021#10Issue 117 - 21 pp.
In this paper, the mathematical interpretation of VOR is derived and a VOR adaptation method is newly proposed. This study of cerebellar inspired adaptive control, which is augmented by the reference model, provides a potential general solution for robotic control. If the reference model is not used, the plant with more poles than zeroes finds it difficult to give a response immediately. The reference model determines the behaviour of the robot. The response of it at high frequency with small-time constant shows the roll-off, low frequency signals not affected. To verify the proposed method of neural control for image stabilisation using a reference model, first, it is briefly introduced and then it is utilized for Matlab and Simulink simulation and experiments. The described cerebellar algorithm has the potential to provide a modular controller for soft robots. Also, it can be applied to generic control tasks, as the force control, or impedance response, or task calibration.
cerebellum , model reference adaptive control , robotics , vestibulo-ocular reflex
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Almaty University of Power Engineering and Telecommunications, Almaty, 050013, Kazakhstan
Academy of Civil Aviation, Almaty, 050049, Kazakhstan
Almaty University of Power Engineering and Telecommunications
Academy of Civil Aviation
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