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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Robust evolving cloud-based controller in normalized data space for heat-exchanger plant
AU - Andonovski, Goran
AU - Blazic, Saso
AU - Angelov, Plamen
AU - Skrjanc, Igor
N1 - ©2015 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
PY - 2015/9
Y1 - 2015/9
N2 - This paper presents an improved version and a modification of Robust Evolving Cloud-based Controller (RECCo). The first modification is normalization of data space in RECCo. As a consequence, some of the evolving and adaptation parameters become independent of the range of the process output signal. Thus the controller tuning is simplified which makes the approach more appealing for the use in practical applications. The data space normalization is general and is used with Euclidean norm, but other distance metrics could also be used. Beside the normalizationnew adaptation scheme of the controller gain is proposed which improves the control performance in the case of a negative initial error in starting phase of the evolving process. At the end, different simulation scenarios are tested and analyzed for further practical implementation of theCloud-based controller into real environments. For that reason a detail simulation study of a plate heat exchanger is performed and different scenarios were analyzed.
AB - This paper presents an improved version and a modification of Robust Evolving Cloud-based Controller (RECCo). The first modification is normalization of data space in RECCo. As a consequence, some of the evolving and adaptation parameters become independent of the range of the process output signal. Thus the controller tuning is simplified which makes the approach more appealing for the use in practical applications. The data space normalization is general and is used with Euclidean norm, but other distance metrics could also be used. Beside the normalizationnew adaptation scheme of the controller gain is proposed which improves the control performance in the case of a negative initial error in starting phase of the evolving process. At the end, different simulation scenarios are tested and analyzed for further practical implementation of theCloud-based controller into real environments. For that reason a detail simulation study of a plate heat exchanger is performed and different scenarios were analyzed.
KW - robust control
KW - evolving
KW - fuzzy
U2 - 10.1109/FUZZ-IEEE.2015.7337992
DO - 10.1109/FUZZ-IEEE.2015.7337992
M3 - Conference contribution/Paper
SN - 9781467374286
SP - 1
EP - 7
BT - Fuzzy Systems (FUZZ-IEEE), 2015 IEEE International Conference on
PB - IEEE
T2 - IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2015)
Y2 - 2 August 2015 through 5 August 2015
ER -