Back to Search

Ultra Wide Band Band Pass Filter

AUTHOR Laharia, Abhishek; Sharma, Krishankant; Laharia Abhishek et al.
PUBLISHER LAP Lambert Academic Publishing (06/21/2013)
PRODUCT TYPE Paperback (Paperback)

Description
This book provide the Detailed Knowledge of the design of Artificial Neural Network (ANN) based PID controller, to realize fast governor action in a power generation plant. The design technique is applied to single area, two area systems, to tune the parameters of the PID controller. Feed forward neural network architecture is chosen for the design of controller, which is trained by a popular back propagation algorithm. Performance of the proposed ANN based Controller, is compared with conventional integral and PID controllers, through dynamic simulation. It is observed that ANN based controller provides better performance. The frame work for interactive learning presented in this Book differs from this used in more established field of interactive evolutionary computation. The main difference is requirement of expert knowledge from neural network area, which makes it a research tool. We hope in future interactive learning of neural networks can be defined enough to be used in real world applications.
Show More
Product Format
Product Details
ISBN-13: 9783659406690
ISBN-10: 3659406694
Binding: Paperback or Softback (Trade Paperback (Us))
Content Language: English
More Product Details
Page Count: 84
Carton Quantity: 84
Product Dimensions: 6.00 x 0.20 x 9.00 inches
Weight: 0.30 pound(s)
Country of Origin: US
Subject Information
BISAC Categories
Technology & Engineering | Electronics - General
Descriptions, Reviews, Etc.
publisher marketing
This book provide the Detailed Knowledge of the design of Artificial Neural Network (ANN) based PID controller, to realize fast governor action in a power generation plant. The design technique is applied to single area, two area systems, to tune the parameters of the PID controller. Feed forward neural network architecture is chosen for the design of controller, which is trained by a popular back propagation algorithm. Performance of the proposed ANN based Controller, is compared with conventional integral and PID controllers, through dynamic simulation. It is observed that ANN based controller provides better performance. The frame work for interactive learning presented in this Book differs from this used in more established field of interactive evolutionary computation. The main difference is requirement of expert knowledge from neural network area, which makes it a research tool. We hope in future interactive learning of neural networks can be defined enough to be used in real world applications.
Show More
Your Price  $51.17
Paperback