Genetic Tuning Scheme of PID Parameters for First-Order Systems with Large Dead Times

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概要

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• PID control schemes have been widely used in most of process control systems. Most of these processes are of ten treated as first-order systems with dead times. And also, in many cases, PID parameters are usually tuned based on the process parameters, i.e., the time constant, the dead time and the process gain. However, since these process parameters can not be obtained exactly, it is well known that it is difficult to find the suitable PID parameters in practice. In this paper, we propose a genetic tuning scheme of PID parameters for first-order systems with large dead times. The authors have already proposed a tuning method of PID parameters using a genetic algorithm (GA), which was based on the relationship between PID control and generalized minimum variance control(GMVC) laws. In practice, for large dead time systems, first-order low pass pre-filters are often used. The proposed method is an extended version of the previously proposed method mentioned above to the system with a pre-filter due to the large dead time, i.e., a tuning method of both PID parameters and the pre-filter using a GA. The proposed control scheme is numerically evaluated on some simulation examples.

• 社団法人電子情報通信学会の論文
• 2000-04-25

著者

• Yamamoto T

  Graduate School Of Engineering Hokkaido University

• Mitsukura Yasue

  The Author Is With The Faculty Of Engineering University Of Tokushima

• YAMAMOTO Toru

  The author is with the Faculty of Education, Hiroshima University

• KANEDA Masahiro

  The author is with the Faculty of Computer Science and Systems Engineering, Okayama Prefectural Univ

• Kaneda M

  The Author Is With The Faculty Of Computer Science And Systems Engineering Okayama Prefectural Unive

• Yamamoto Toru

  The Author Is With The Faculty Of Education Hiroshima University

関連論文

• Design of a Self-Tuning PID Controller Using Evolutionary Computation and Its Experimental Evaluation
• Memory-based IMC Tuning of PID Controllers for Nonlinear Systems
• Memory-based IMC Tuning of PID Controllers for Nonlinear Systems
• A Design of Neural-Net Based PID Controllers with Evolutionary Computation(Systems and Control)
• A Design of Model Driven Cascade PID Controllers Using a Neural Network(Nonlinear Theory and its Applications)
• Genetic Tuning Scheme of PID Parameters for First-Order Systems with Large Dead Times

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