The Experts below are selected from a list of 309 Experts worldwide ranked by ideXlab platform

O.d.i. Nwokah - One of the best experts on this subject based on the ideXlab platform.

  • Robust multivariable turbofan Engine Control: a case study
    Proceedings of 1994 33rd IEEE Conference on Decision and Control, 1
    Co-Authors: R.e. Nordgren, Z. Gastineau, S. Adibhatla, G.s. Grewal, O.d.i. Nwokah
    Abstract:

    The application of robust Controller design techniques to aircraft turbofan Engine Control problems has a long and intensive history. These applications have revealed many of the strengths and weaknesses of the many solution techniques. In this paper, two robust Control techniques, /spl mu/-synthesis and the quantitative Nyquist array, are applied to the GE16 aircraft turbofan Engine Control problem for the purpose of designing a full flight envelope Controller capable of meeting robust performance specifications. Performance and implementation issues of the two Controllers are explored and compared to a Control law based upon gain scheduling. >

Sibylle Schwartze-eidam - One of the best experts on this subject based on the ideXlab platform.

Johan Karlsson - One of the best experts on this subject based on the ideXlab platform.

  • Derivation of Diagnostic Requirements for a Distributed UAV Turbofan Engine Control System
    Journal of Engineering for Gas Turbines and Power, 2008
    Co-Authors: Olof Hannius, Dan Ring, Johan Karlsson
    Abstract:

    This paper presents a method for deriving requirements for the efficiency of diagnostic functions in distributed electronic turbofan Engine Control systems. Distributed Engine Control systems consist of sensor, actuator, and Control unit nodes that exchange data over a communication network. The method is applicable to Engine Control systems that are partially redundant. Traditionally, turbofan Engine Control systems use dual channel solutions in which all units are duplicated. Our method is intended for analyzing the diagnostic requirements for systems in which a subset of the sensors and the actuators is nonredundant. Such systems rely on intelligent monitoring and analytical redundancy to detect and tolerate failures in the nonredundant units. These techniques cannot provide perfect diagnostic coverage and, hence, our method focuses on analyzing the impact of nonperfect diagnostic coverage on the reliability and safety of distributed Engine Control systems. The method is based on a probabilistic analysis that combines fault trees and Markov chains. The input parameters for these models include failure rates as well as several coverage factors that characterize the performance of the diagnostic functions. Since the use of intelligent monitoring can cause false alarms, i.e., an error is falsely indicated by a diagnostic function, the parameters also include a false alarm rate. The method was used to derive the diagnostic requirements for a hypothetical unmanned aerial vehicle Engine Control system. Given the requirement that an Engine failure due to the Control system is not allowed to occur more than ten times per million hours, the diagnostic functions in a node must achieve 99% error coverage for transient faults and 90–99% error coverage for permanent faults. The system-level diagnosis must achieve 90–95% detection coverage for node failures, which are not detected by the nodes themselves. These results are based on the assumption that transient faults are 100 times more frequent than permanent faults. It is important to have a method for deriving probabilistic requirements on diagnostic functions for Engine Control systems that rely on analytical redundancy as a means to reduce the hardware redundancy. The proposed method allows us to do this using an existing tool (FAULTTREE+) for safety and reliability analysis.

Alireza Behbahani - One of the best experts on this subject based on the ideXlab platform.

  • Lightweight optical aero-Engine Control network
    Optical Fiber Communication Conference National Fiber Optic Engineers Conference 2011, 2011
    Co-Authors: Rui Wang, Alireza Behbahani, Richard J. Black, Behzad Moslehi, Biswanath Mukherjee
    Abstract:

    A novel communication platform, AViAtion real-Time Adaptive Ring (AVATAR), using Ethernet-over-WDM is proposed to support real-time aero-Engine Control network. Optimal frame layout for different network configurations are used to guide the design.

  • Distributed Engine Control Design Considerations
    46th AIAA ASME SAE ASEE Joint Propulsion Conference & Exhibit, 2010
    Co-Authors: Walter Merrill, Jong-han Kim, Sanjay Lall, Steve Majerus, Daniel S. Howe, Alireza Behbahani
    Abstract:

    vi Various distributed Engine Control architectures are presented. Different elements of this architecute include semi-autonomous (aka 'smart') nodes, digital network communications, data concentrators and electronic Controllers. To survive the harsh environment of a turbine Engine application, a distributed Engine Control will require high temperature electronics for its implementation. Several high temperature integrated circuits and a semi- autonomous node architecture which incorporates the electronics are presented. These high temperature circuits provide sensor measurement and actuator Control interfaces, digital communication, and voltage Control and distribution. Next, the authors differentiate between distributed and decentralized Controllers and develop a decentralized Control design approach based on optimal Control theory which can be evolved toward an analysis tool for the Control performance of various types of decentralized network configurations.

  • Stability Analysis of Distributed Engine Control Systems Under Communication Packet Drop
    44th AIAA ASME SAE ASEE Joint Propulsion Conference & Exhibit, 2008
    Co-Authors: Rama K. Yedavalli, Rohit K. Belapurkar, Alireza Behbahani
    Abstract:

    ‡Currently, Full Authority Digital Engine Control (FADEC), based on a centralized architecture framework is being widely used for gas turbine Engine Control. However, current FADEC is not able to meet the increased burden imposed by the advanced intelligent propulsion system concepts. This has necessitated development of the Distributed Engine Control system (DEC). FADEC based on Distributed Control Systems (DCS) offers modularity, improved Control systems prognostics and fault tolerance along with reducing the impact of hardware obsolescence. Some of the challenges to be dealt with are selection of communication architecture, high temperature electronics and logical functional partitioning of centralized Controller. In this paper, we propose Decentralized Distributed Full Authority Digital Engine Control (D 2 FADEC) based on a two level decentralized Control framework. The effect of decentralized Controller on system stability and robustness through the Packet Dropping Margin (PDM) has been studied. A design method is proposed to decouple the centralized Controller into different subsystems, thus reducing the effect of interactions between the subsystems. It is shown that PDM is largely dependent on the closed loop Controller structure; hence use of a Controller in a decentralized framework improves the PDM. Also, a F100 gas turbine Engine example is used to show that PDM can be improved by partitioning the centralized system.

  • Stability Analysis of Distributed Engine Control Systems Under Communication Packet Drop (Postprint)
    2008
    Co-Authors: Rama K. Yedavalli, Rohit K. Belapurkar, Alireza Behbahani
    Abstract:

    Abstract : Currently, Full Authority Digital Engine Control (FADEC), based on a centralized architecture framework is being widely used for gas turbine Engine Control. However, current FADEC is not able to meet the increased burden imposed by the advanced intelligent propulsion system concepts. This has necessitated development of the Distributed Engine Control system (DEC). FADEC based on Distributed Control Systems (DCS) offers modularity, improved Control systems prognostics and fault tolerance along with reducing the impact of hardware obsolescence. Some of the challenges to be dealt with are selection of communication architecture, high temperature electronics and logical functional partitioning of centralized Controller.

  • Status, Vision, and Challenges of an Intelligent Distributed Engine Control Architecture (Postprint)
    2007
    Co-Authors: Alireza Behbahani, Bobbie Hegwood, Dennis E. Culley, Sheldon Carpenter, Bill Mailander, Bert Smith, Christopher Darouse, Tim Mahoney, Ronald Quinn, Gary Battestin
    Abstract:

    Abstract : A Distributed Engine Control Working Group (DECWG) consisting of the Department of Defense (DoD), the National Aeronautics and Space Administration (NASA)-Glenn Research Center (GRC) and industry has been formed to examine the current and future requirements of propulsion Engine systems. The scope of this study will include an assessment of the paradigm shift from centralized Engine Control architecture to an architecture based on distributed Control utilizing open system standards. Included will be a description of the work begun in the 1990's, which continues today, followed by the identification of the remaining technical challenges which present barriers to on-Engine distributed Control.

R.e. Nordgren - One of the best experts on this subject based on the ideXlab platform.

  • Robust multivariable turbofan Engine Control: a case study
    Proceedings of 1994 33rd IEEE Conference on Decision and Control, 1
    Co-Authors: R.e. Nordgren, Z. Gastineau, S. Adibhatla, G.s. Grewal, O.d.i. Nwokah
    Abstract:

    The application of robust Controller design techniques to aircraft turbofan Engine Control problems has a long and intensive history. These applications have revealed many of the strengths and weaknesses of the many solution techniques. In this paper, two robust Control techniques, /spl mu/-synthesis and the quantitative Nyquist array, are applied to the GE16 aircraft turbofan Engine Control problem for the purpose of designing a full flight envelope Controller capable of meeting robust performance specifications. Performance and implementation issues of the two Controllers are explored and compared to a Control law based upon gain scheduling. >