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Journal of Automation and Information Sciences

Publication de 12  numéros par an

ISSN Imprimer: 1064-2315

ISSN En ligne: 2163-9337

SJR: 0.173 SNIP: 0.588 CiteScore™:: 2

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Methods of Hardware and Software Realization of Adaptive Neural Network PID Controller on FPGA-Chip

Volume 43, Numéro 4, 2011, pp. 70-77
DOI: 10.1615/JAutomatInfScien.v43.i4.80
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RÉSUMÉ

The methods of hardware and software implementation of adaptive neural network PID controller on FPGA-chip is considered, the stepwise algorithm of such controller synthesis is presented. The model of the controller is presented in the System Generator for DSP, calculations of optimal bit network of data which ensures correct operation of the PID controller are performed.

CITÉ PAR
  1. Kravets Peter, Shymkovych Volodymyr, Hardware Implementation Neural Network Controller on FPGA for Stability Ball on the Platform, in Advances in Computer Science for Engineering and Education II, 938, 2020. Crossref

  2. Doroshenko А.Yu., Shymkovych V.M. , Fedorenko V.O. , Software means of modeling of the vector type of reactive engine control system, PROBLEMS IN PROGRAMMING, 2-3, 2018. Crossref

  3. Shymkovych Volodymyr, Niechkina Veronika, The criterion for determining the buffering time of the measuring channel for smoothing the variable changes of the sensor signal, 2020 IEEE 7th International Conference on Energy Smart Systems (ESS), 2020. Crossref

  4. Kravets Petro, Nevolko Viacheslav, Shymkovych Volodymyr, Shymkovych Lyubov, Synthesis of High-Speed Neuro-Fuzzy-ControllersBased on FPGA, 2020 IEEE 2nd International Conference on Advanced Trends in Information Theory (ATIT), 2020. Crossref

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