An LMI Design of an Observer-based Fuzzy PSS
IFAC • 2008
معلومات البحث
المؤلفون
M. Soliman, A-L Elshafei, F. Bendary, W. Mansour
الكلمات المفتاحية
Intelligent control of power systems, modelling, operation and control of
power systems, control system design
المجلة العلمية
IFAC
الناشر
IFAC
المجلد
Not Available
العدد
Not Available
الصفحات
Not Available
publication.type
International
رابط البحث
Not Available
المواد المرفقة
Not Available
الملخص
Power systems are highly nonlinear systems that exhibit undesirable oscillations following disturbances.
Power system stabilizers (PSS) are usually incorporated to provide auxiliary excitation signals to damp these
oscillations. Our objective is to improve the PSS performance via the use of fuzzy logic and LMI techniques. A
power system is viewed as a polytopic model that can be adequately represented by a Takagi-Sugeno fuzzy system. A
power system stabilizer based on the parallel distributed control principle is suggested. Typically, speed
measurements are used as feedback signals. Consequently, a fuzzy observer is included to estimate the unmeasured
states. LMI conditions that guarantee the stability and robust pole clustering of the closed loop system are derived.
Simulation results of both single-machine and multi-machine models confirm the effectiveness of the proposed
algorithm
Power system stabilizers (PSS) are usually incorporated to provide auxiliary excitation signals to damp these
oscillations. Our objective is to improve the PSS performance via the use of fuzzy logic and LMI techniques. A
power system is viewed as a polytopic model that can be adequately represented by a Takagi-Sugeno fuzzy system. A
power system stabilizer based on the parallel distributed control principle is suggested. Typically, speed
measurements are used as feedback signals. Consequently, a fuzzy observer is included to estimate the unmeasured
states. LMI conditions that guarantee the stability and robust pole clustering of the closed loop system are derived.
Simulation results of both single-machine and multi-machine models confirm the effectiveness of the proposed
algorithm
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