TY - GEN
T1 - Fuzzy controllers design using space-filling curves
AU - Elshafei-Ahmed, M.
AU - Ahmed, M. S.
PY - 1998
Y1 - 1998
N2 - In this paper we present a clustering technique for fuzzy rules based on Hilbert Space-filling Curves (SFC). SFC scans an n-dimensional space and reduces it to a curve, i.e. a one-dimensional line. The paper introduces first the Hilber Space-filling curves, and outlines algorithms for clustering and adaptive clustering which demonstrate the SFC efficient self-organizing features. We then propose a SFC fuzzy inference model based on clustering the object space. The SFC fuzzy model is then used to design a fuzzy controller. The proposed method achieves a dramatic reduction of the complexity of fuzzy controller by reducing the multivariable fuzzification problem to a one dimentional space.
AB - In this paper we present a clustering technique for fuzzy rules based on Hilbert Space-filling Curves (SFC). SFC scans an n-dimensional space and reduces it to a curve, i.e. a one-dimensional line. The paper introduces first the Hilber Space-filling curves, and outlines algorithms for clustering and adaptive clustering which demonstrate the SFC efficient self-organizing features. We then propose a SFC fuzzy inference model based on clustering the object space. The SFC fuzzy model is then used to design a fuzzy controller. The proposed method achieves a dramatic reduction of the complexity of fuzzy controller by reducing the multivariable fuzzification problem to a one dimentional space.
UR - http://www.scopus.com/inward/record.url?scp=0342495866&partnerID=8YFLogxK
U2 - 10.1109/ACC.1998.707339
DO - 10.1109/ACC.1998.707339
M3 - Conference contribution
AN - SCOPUS:0342495866
SN - 0780345304
SN - 9780780345300
T3 - Proceedings of the American Control Conference
SP - 1855
EP - 1859
BT - Proceedings of the 1998 American Control Conference, ACC 1998
ER -