Design of a Performance-Driven CMAC PID Controller

Yuntao LIAO; Takuya KINOSHITA; Kazushige KOIWAI; Toru YAMAMOTO

doi:10.1587/transfun.E100.A.2963

Design of a Performance-Driven CMAC PID Controller

Yuntao LIAO, Takuya KINOSHITA, Kazushige KOIWAI, Toru YAMAMOTO

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Summary :

In industrial control processes, control performance influences the quality of products and utilization efficiency of energy; hence, the controller is necessarily designed according to user-desired control performance. Ideal control performance requires fast response for transient state and maintaining user-specified control performance for steady state. Hence, an algorithm to tune controller parameters to match the requirements for transient state and steady state is proposed. Considering the partial learning ability of the cerebellar model articulation controller (CMAC) neural network, it is utilized as a “tuner” of controller parameters in this study, since then the controller parameters can be tuned in both transient and steady states. Moreover, the fictitious reference iterative tuning (FRIT) algorithm is combined with CMAC in order to avoid problems, which may be caused by system modeling error and by using only a set of closed-loop data, the desired controller can be calculated in an off-line manner. In addition, the controller selected is a proportional-integral-derivative (PID) controller. Finally, the effectiveness of the proposed method is numerically verified by using some simulation and experimental examples.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E100-A No.12 pp.2963-2971

Publication Date: 2017/12/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E100.A.2963

Type of Manuscript: PAPER

Category: Systems and Control

Authors

Yuntao LIAO
  Hiroshima University
Takuya KINOSHITA
  Hiroshima University
Kazushige KOIWAI
  Hiroshima University
Toru YAMAMOTO
  Hiroshima University

Keyword

PID, CMAC, FRIT, performance driven, neural network, minimum variance control (MVC)

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Yuntao LIAO, Takuya KINOSHITA, Kazushige KOIWAI, Toru YAMAMOTO, "Design of a Performance-Driven CMAC PID Controller" in IEICE TRANSACTIONS on Fundamentals, vol. E100-A, no. 12, pp. 2963-2971, December 2017, doi: 10.1587/transfun.E100.A.2963.
Abstract: In industrial control processes, control performance influences the quality of products and utilization efficiency of energy; hence, the controller is necessarily designed according to user-desired control performance. Ideal control performance requires fast response for transient state and maintaining user-specified control performance for steady state. Hence, an algorithm to tune controller parameters to match the requirements for transient state and steady state is proposed. Considering the partial learning ability of the cerebellar model articulation controller (CMAC) neural network, it is utilized as a “tuner” of controller parameters in this study, since then the controller parameters can be tuned in both transient and steady states. Moreover, the fictitious reference iterative tuning (FRIT) algorithm is combined with CMAC in order to avoid problems, which may be caused by system modeling error and by using only a set of closed-loop data, the desired controller can be calculated in an off-line manner. In addition, the controller selected is a proportional-integral-derivative (PID) controller. Finally, the effectiveness of the proposed method is numerically verified by using some simulation and experimental examples.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E100.A.2963/_p

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@ARTICLE{e100-a_12_2963,
author={Yuntao LIAO, Takuya KINOSHITA, Kazushige KOIWAI, Toru YAMAMOTO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Design of a Performance-Driven CMAC PID Controller},
year={2017},
volume={E100-A},
number={12},
pages={2963-2971},
abstract={In industrial control processes, control performance influences the quality of products and utilization efficiency of energy; hence, the controller is necessarily designed according to user-desired control performance. Ideal control performance requires fast response for transient state and maintaining user-specified control performance for steady state. Hence, an algorithm to tune controller parameters to match the requirements for transient state and steady state is proposed. Considering the partial learning ability of the cerebellar model articulation controller (CMAC) neural network, it is utilized as a “tuner” of controller parameters in this study, since then the controller parameters can be tuned in both transient and steady states. Moreover, the fictitious reference iterative tuning (FRIT) algorithm is combined with CMAC in order to avoid problems, which may be caused by system modeling error and by using only a set of closed-loop data, the desired controller can be calculated in an off-line manner. In addition, the controller selected is a proportional-integral-derivative (PID) controller. Finally, the effectiveness of the proposed method is numerically verified by using some simulation and experimental examples.},
keywords={},
doi={10.1587/transfun.E100.A.2963},
ISSN={1745-1337},
month={December},}

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TY - JOUR
TI - Design of a Performance-Driven CMAC PID Controller
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2963
EP - 2971
AU - Yuntao LIAO
AU - Takuya KINOSHITA
AU - Kazushige KOIWAI
AU - Toru YAMAMOTO
PY - 2017
DO - 10.1587/transfun.E100.A.2963
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E100-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2017
AB - In industrial control processes, control performance influences the quality of products and utilization efficiency of energy; hence, the controller is necessarily designed according to user-desired control performance. Ideal control performance requires fast response for transient state and maintaining user-specified control performance for steady state. Hence, an algorithm to tune controller parameters to match the requirements for transient state and steady state is proposed. Considering the partial learning ability of the cerebellar model articulation controller (CMAC) neural network, it is utilized as a “tuner” of controller parameters in this study, since then the controller parameters can be tuned in both transient and steady states. Moreover, the fictitious reference iterative tuning (FRIT) algorithm is combined with CMAC in order to avoid problems, which may be caused by system modeling error and by using only a set of closed-loop data, the desired controller can be calculated in an off-line manner. In addition, the controller selected is a proportional-integral-derivative (PID) controller. Finally, the effectiveness of the proposed method is numerically verified by using some simulation and experimental examples.
ER -