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Design and rule base reduction of a fuzzy filter for the estimation of motor currents
در صورت بروز مشکل هنگام پرداخت هزینه به آیدی تلگرام بنده پیام دهید.
@adota
مقدمه مقاله به صورت زیر است.
Fuzzy systems have been used extensively and successfully in control systems over
the past few decades, but have been applied much less often to ®ltering problems. This
is somewhat surprising in view of the dual relationship between control and estima
tion. This paper discusses and demonstrates the application of fuzzy ®ltering to motor
winding current estimation in permanent magnet synchronous motors. Motor winding
current estimation is an important problem because in order to implement eective
closed-loop control, a good estimation of the current is needed. Motor winding
currents are notoriously noisy because of electrical noise in the motor drive. We use a
fuzzy system with correlation-product inference and centroid defuzzi®cation for motor
winding current estimation. With the assumption that the membership functions are
triangular (but not necessarily symmetric), we then optimize the membership functions
using gradient descent. Next we use singular value decomposition to reduce the rule
base for the fuzzy ®lter. Rule base reduction can be important for fuzzy systems in
those cases where the fuzzy system needs to be implemented in real time. This is
especially true with regard to fuzzy ®ltering in a real time motor controller. The
methods discussed in this paper are demonstrated on real motor winding currents that
were collected with a digital oscilloscope. It is demonstrated that fuzzy techniques
provide a feasible approach to motor current estimation, that gradient descent
optimization improves the performance of the ®lter, and that rule base reduction
results in a relatively small degradation of ®lter performance. Ó 2000 Elsevier Science
Inc. All rights reserved
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