Distributed control architecture for aircraft fluid management

Smartfuel is a research project from a European Commission Framework Programme. The project aims to move away from a centralized control architecture for aircraft fuel management. The controlling functionality (originally located in a central computer) in a Distributed Aircraft Fuel Management System (DAFMS) is partially deployed in networked Smart Fuel Components (SFCs). SFCs are mechatronic fuel components that can make their decisions by themselves based on the DAFMS states and the sequence of actions of the DAFMS operation. Smartfuel considers three DAFMS operation modes: pressure refueling, engine supply, and fuel transfer. This paper discusses the investigation work done toward developing the above DAFMS. The discussion includes computer models, laboratory prototypes, and an aircraft rig as well as a real-scale helicopter used to evaluate the DAFMS approach. Potential use of the approach proposed for spacecraft and concluding remarks are also discussed.

[1]  T. G. Davis Aircraft fuel system simulation , 1990, IEEE Conference on Aerospace and Electronics.

[2]  Albert Helfrick The centennial of avionics: Our 100-year trek to performance-based navigation , 2015, IEEE Aerospace and Electronic Systems Magazine.

[3]  N. Rittmannsberger,et al.  Antilock Braking System And Traction Control , 1988, International Congress on Transportation Electronics,.

[4]  T. Führer,et al.  Time Triggered Communication on CAN ( Time Triggered CAN-TTCAN ) , 2000 .

[5]  M.A. Seminario,et al.  Experimental Results with a New Distributed Aircraft Fuel Control System Which Uses Smart Fieldbus Components , 2006, 2006 ieee/aiaa 25TH Digital Avionics Systems Conference.

[6]  G. Biswas,et al.  Model-based fault-adaptive control of complex dynamic systems , 2003, Proceedings of the 20th IEEE Instrumentation Technology Conference (Cat. No.03CH37412).

[7]  Andrew J. Chipperfield,et al.  Modelling Control Systems Using IEC 61499 , 2001 .

[8]  Gregory J. Pottie,et al.  Principles of Embedded Networked Systems Design , 2005 .

[9]  George N. Saridis,et al.  Self-organizing control of stochastic systems , 1977 .

[10]  Charles R. McLean,et al.  Hierarchical Control for Robots and Teleoperators , 1985 .

[11]  Agostino Poggi,et al.  Multiagent Systems , 2006, Intelligenza Artificiale.

[12]  Carlos C. Insaurralde,et al.  Computer Tool With a Code Generator for Avionic Distributed Fuel Control Systems With Smart Sensors and Actuators , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[13]  Ernest R. Tello Object-oriented programming for artificial intelligence - a guide to tools and system design , 1989 .

[14]  Salim Hariri,et al.  Self-adapting, self-optimizing runtime management of Grid applications using PRAGMA , 2003, Proceedings International Parallel and Distributed Processing Symposium.

[15]  J.F. Jimenez,et al.  CANbus-based distributed fuel system with smart components , 2008, IEEE Transactions on Aerospace and Electronic Systems.

[16]  Scott Alan Liljenberg Modeling and Stability Analysis of Thermoacoustic Instabilities in Gas Turbine Combustor Sections , 2000 .

[17]  A Koestler,et al.  Ghost in the Machine , 1970 .

[18]  Carlos C. Insaurralde,et al.  Ground-tested control architecture for distributed aircraft fuel management , 2016, 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC).

[19]  Carlos C. Insaurralde,et al.  IEC 61499 Model for Avionics Distributed Fuel Systems with Networked Embedded Holonic Controllers , 2006, 2006 IEEE Conference on Emerging Technologies and Factory Automation.

[20]  Julia Eichmann Real Time Systems Scheduling Analysis And Verification , 2016 .

[21]  T. Pirttioja Agent-Augmented Process Automation System , 2002 .

[22]  Paulo Leitão,et al.  An agile and adaptive holonic architecture for manufacturing control , 2004 .