Weight Initialization on Neural Network for Neuro PID Controller: Case study

Theertham Akilesh Sai, HeeHyol Lee

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Neuro PID controller has been widely used in control field in recent times. Random weight initialization is used in the Neuro PID controller. The impact of various weight initialization has not been studied in the Neuro PID controller. The weight initialization methods such as Xavier initialization and He initialization have been proven to be effective in faster convergence in neural network. This paper investigated a weight initialization concept in Neuro PID controller by case studying with zero initialization, constant initialization, Gaussian distributed initialization, uniform distributed initialization, He initialization, and Xavier initialization in typical first-order lag elements, integrator elements, and dead time elements to obtain suitable initialization of weight coefficients, which reduces settling time for the neural network.

本文言語English
ホスト出版物のタイトル2018 International Conference on Information and Communication Technology Robotics, ICT-ROBOT 2018
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781728119960
DOI
出版ステータスPublished - 2018 11 27
イベント2018 International Conference on Information and Communication Technology Robotics, ICT-ROBOT 2018 - Busan, Korea, Republic of
継続期間: 2018 9 62018 9 8

Other

Other2018 International Conference on Information and Communication Technology Robotics, ICT-ROBOT 2018
CountryKorea, Republic of
CityBusan
Period18/9/618/9/8

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Communication

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