TY - GEN
T1 - Intelligent digital redesign for nonlinear systems with parametric uncertainties
AU - Sung, Hwa Chang
AU - Park, Jin Bae
AU - Joo, Young Hoon
PY - 2006
Y1 - 2006
N2 - This paper presents intelligent digital redesign (IDR) method of global approach for fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(T-S) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a T-S fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.
AB - This paper presents intelligent digital redesign (IDR) method of global approach for fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(T-S) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a T-S fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=34250753413&partnerID=8YFLogxK
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U2 - 10.1109/SICE.2006.314822
DO - 10.1109/SICE.2006.314822
M3 - Conference contribution
AN - SCOPUS:34250753413
SN - 8995003855
SN - 9788995003855
T3 - 2006 SICE-ICASE International Joint Conference
SP - 3150
EP - 3155
BT - 2006 SICE-ICASE International Joint Conference
T2 - 2006 SICE-ICASE International Joint Conference
Y2 - 18 October 2006 through 21 October 2006
ER -