Neural Network based Throttle Controller for Compressor | Neural Network based Throttle Controller for Compressor

Divya M N

ISBN 10: 6207465849 / ISBN 13: 9786207465842

Published by LAP LAMBERT Academic Publishing, 2024

About this Item

Neural Network based Throttle Controller for Compressor | Neural Network based Throttle Controller for Compressor | Divya M N | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207465842 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.

Seller Inventory # 128936080

Bibliographic Details

• Title: Neural Network based Throttle Controller for Compressor | Neural Network based Throttle Controller for Compressor
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2024
• Language: English
• ISBN 10: 6207465849
• ISBN 13: 9786207465842
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 4D millimeters 220 millimeters width by 150 millimeters height by 4 millimeters depth
• Weight: 96 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

The centrifugal Compressor is used in various industries, including oil, aerospace, and gas facilities, to increase pressure and oil output. If the Compressors are failed, then the entire system's production will be halted.The primary objective is to model the centrifugal Compressor with Anti-surge control (ASC) mechanism using neural networks to avoid surge issues and improve performance metrics. Different controllers like PID controller, followed by Fuzzy logic controller (FLC), Neuro-fuzzy controller (NFC) are incorporated in Anti surge control(ASC) mechanism for Compressor recycle system to realize the performance comparison. The modelling of the CRS with ASC mechanism is carried out using MATLAB Simulink environment. The simulation results like different flow rates, suction and plenum pressures, speed, and compressor maps are realized in detail for all the controller designs. The performance metrics error responses are analyzed in detail for CRS with ASC mechanism using different controllers. Based on the NNPC output response in the ASC mechanism of the CRS system, the OP position is adjacent to the Surge control line (SCL).