Fuzzy PID Iterative learning control for a class of Nonlinear Systems with Arbitrary Initial Value

DOI

10.2991/emcm-16.2017.60How to use a DOI?

Keywords

Nonlinear system; Arbitrary initial value; Fuzzy PID Iterative learning control; Norm theory. Operator theory

Abstract

Aiming at a class of nonlinear systems running repeatedly in the study of the convergence of iterative learning control, a PID fuzzy iterative learning control algorithm has been proposed in the arbitrary initial value using fuzzy PID control algorithm, using traditional experience PID parameters by reference, and experiencing real-time correction of PID parameters, generating higher precision fuzzy PID learning law. The use of operator theory and the theory of convergence norm has been proved by simulation experiment, nonlinear systems under arbitrary initial conditions, the use of fuzzy PID iterative learning control algorithm, the system converges faster, higher tracking accuracy, the output of the error curve faster tends to zero. The results of the demonstrates the effectiveness of the algorithm.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaohong Hao
AU  - Dongjiang Wang
PY  - 2017/02
DA  - 2017/02
TI  - Fuzzy PID Iterative learning control for a class of Nonlinear Systems with Arbitrary Initial Value
BT  - Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcm-16.2017.60
DO  - 10.2991/emcm-16.2017.60
ID  - Hao2017/02
ER  -