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Robot algorithm based on neural network and intelligent predictive control

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Abstract

With the improvement of industrial control requirements and the development of control theory and computer technology, it is more and more urgent to study the intelligent predictive control algorithm with good control effect, strong robustness and suitable for more complicated industrial processes. This paper proposes a novel intelligent predictive control scheme that uses a neural network intelligent predictive controller to control the force/position of the robot. The controller of this neural network can arbitrarily approach the uncertain object of the industrial robot without knowing the exact structure of the system. At the same time, due to the addition of intelligent predictive control, the system is easy to calculate online and the quality of control is improved. It can be seen from the simulation results of the robot that the traditional PID can not solve the uncertain object well. With the controller designed in this paper, the robustness and rapidity of the system are improved to some extent, and good control accuracy and control effects are achieved.

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Authors and Affiliations

  1. Department of Publishing and Media, Chongqing Business Vocational College, Chongqing, 401331, China

    Yini Wang

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  1. Yini Wang
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Correspondence to Yini Wang.

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Wang, Y. Robot algorithm based on neural network and intelligent predictive control. J Ambient Intell Human Comput 11, 6155–6166 (2020). https://doi.org/10.1007/s12652-019-01622-6

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  • DOI: https://doi.org/10.1007/s12652-019-01622-6

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