@inproceedings{6225ccc16ba34d98ae39a448838d25c7,
title = "Automatic design of multivariable QFT control system via evolutionary computation",
abstract = "This paper proposes a multi-objective evolutionary automated design methodology for multivariable QFT control systems. Unlike existing manual or convex optimisation based QFT design approaches, the{\textquoteright}intelligent{\textquoteright} evolutionary technique is capable of automatically evolving both the nominal controller and pre-filter simultaneously to meet all performance requirements in QFT, without going through the conservative and sequential design stages for each of the multivariable sub-systems. In addition, it avoids the need of manual QFT bound computation and trial-and-error loop-shaping design procedures, which is particularly useful for unstable or non-minimum phase plants for which stabilising controllers maybe difficult to be synthesised. Effectiveness of the proposed QFT design methodology is validated upon a benchmark multivariable system, which offers a set of low-order Pareto optimal controllers that satisfy all the required closed-loop performances under practical constraints.",
author = "Tan, {K. C.} and Lee, {T. H.} and Khor, {E. F.}",
year = "2000",
month = apr,
doi = "10.1007/3-540-45561-2_18",
language = "English",
isbn = "978-3-540-67353-8",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Berlin Heidelberg",
pages = "178--194",
editor = "Cagnoni, {Stefano }",
booktitle = "Real-World Applications of Evolutionary Computing",
note = "EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight ; Conference date: 17-04-2000 Through 17-04-2000",
}