A Design of Neural-Net Based PID Controllers with Evolutionary Computation

• SUZUKI Michiyo

  Department of Artificial Complex Systems Engineering, Graduate School of Engineering, Hiroshima University

• YAMAMOTO Toru

  Department of Technology and Information Education, Graduate School of Education, Hiroshima University

• TSUJI Toshio

  Department of Artificial Complex Systems Engineering, Graduate School of Engineering, Hiroshima University

Abstract

PID control schemes have been widely used for many industrial processes, which can be represented by nonlinear systems. In this paper a new scheme for neural-net based PID controllers is presented. The connection weights and some parameters of the sigmoidal functions of the neural network are adjusted using a real-coded genetic algorithm. The effectiveness of the newly proposed control scheme for nonlinear systems is numerically evaluated using a simulation example.

Journal

• IEICE transactions on fundamentals of electronics, communications and computer sciences

  IEICE transactions on fundamentals of electronics, communications and computer sciences 87 (10), 2761-2768, 2004-10-01

  The Institute of Electronics, Information and Communication Engineers

Keywords

• PID control
• neural network
• genetic algorithm

Details

• CRID: 1573950402231512832
• NII Article ID: 110003212800
• NII Book ID: AA10826239
• ISSN: 09168508
• Text Lang: en
• Data Source:
  • CiNii Articles