1 / 16

Reconfigurable Control Strategies: Towards Fault – Tolerant and High – Confidence Systems

Reconfigurable Control Strategies: Towards Fault – Tolerant and High – Confidence Systems. George Vachtsevanos Georgia Institute of Technology Atlanta GA 30332-0250 SWAN ’06 The University of Texas at Arlington. December 7 – 9, 2006. Flight Results – Bob Up. Collective Failure Scenario.

kolina
Download Presentation

Reconfigurable Control Strategies: Towards Fault – Tolerant and High – Confidence Systems

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Reconfigurable Control Strategies: Towards Fault – Tolerant and High – Confidence Systems George Vachtsevanos Georgia Institute of Technology Atlanta GA 30332-0250 SWAN ’06 The University of Texas at Arlington December 7 – 9, 2006

  2. Flight Results – Bob Up

  3. Collective Failure Scenario

  4. The Problem Nominal capability Maneuverability Human pilots Degraded capability Reconfig-urable flightcontrol FTC Speed Unmanned aerial vehicles require a fault-tolerant control (FTC) architecture that allows them to generate and track safe flight paths before and after the occurrence of a fault. “Improving UAV reliability is the single most immediate and long reaching need to ensure their success.” - OSD UAV Roadmap 2002-2027

  5. The Anatomy of a Failure 30 mins into flight the helicopter with crew autorotates into the sea SH-60 grounded for IGB servicing Hydraulic fluid swapped for engine oil during maintenance More volatile lubricant evaporates increasing friction IGB output bearing overheats Bearing fails from excessive heat SH-60 loses tail-rotor authority Hydraulic Fluid Runs Red by LCdr. Patrick Kennedy Mech, Winter 2001

  6. Aircraft Mishaps/Failure Modes “Retired Marine Lt. Gen. Bernard Trainor said the issue of aging aircraft is a constant complaint of all branches of service.” Atlanta Journal Constitution April 27, 2002

  7. Testing, Modeling, and Reasoning Architecture for Fault Diagnosis and Failure Prognosis • Prevent unscheduled maintenance • Assist the pilot in making intelligent • decisions about air-worthiness VMEP/ HUMS modules Intermediate Gearbox (IGB) fitted with VMEP sensors to monitor components Testing/ Seeded Fault Data Modeling Reasoning Architecture for Diagnosis-Prognosis

  8. The Fault Diagnosis/Prognosis Architecture

  9. Space Engine Fault Accommodation Actuator Commands Rudder Controllers Run-Time Demo System Integrated Flight Control System Logic (From Task 5) Prognostic & Diagnostic Algorithms (From Task 4) Actuator Performance Data Elevon Controllers Model Validation (Task 3) Body FlapControllers Component Degradation and System Performance Model (From Task 2) System Requirements (Task 1)

  10. Proposed Architecture

  11. Helicopter Active System Restructuring Wcom Wcomdcoll Long. Cyclic dlon Lateral Cyclic dlat Collective Pitch dcoll Tail Rotor Pitch dtr Main Rotor RPMWcom S/P Actuator A dA S/P Actuator B dB S/P Actuator C dC Tail Rotor Pitch dtr Main Rotor RPMWcom • RPM control • Collective • Tail rotor • Swashplate actuators Active Control: Long. Cyclic dlon Lateral Cyclic dlat Collective Pitch dcoll Tail Rotor Pitch dtr Long. Cyclic dlon Lateral Cyclic dlat Collective Pitch dcoll Tail Rotor Pitch dtr S/P Actuator A dA S/P Actuator B dB S/P Actuator C dC Tail Rotor Pitch dtr Alternate means of restructuring employ: tandem rotors, stabilator control, individual blade control, jettisoning of stores

  12. Mission Adaptation • Adapts the position, velocity, acceleration, and/or jerk for the assigned waypoints • Provides a simple exportable model (HURT) • Implies a change to the aircraft time of arrival • With or without reconfigurable path planning

  13. Reconfigurable Flight Control RPM sensor: Feedback Linearization: - Plant Inverted Model Reference Model + Baseline controller AdaptiveNeuralNetwork PD

  14. Flight Results - Stuck Collective

  15. Challenges for Control Engineers • Robust, reliable and timely fault diagnosis and prognosis • Interface requirements to system controllers • System design to accommodate fault isolation, system restructuring and control reconfiguration • Control reconfiguration technologies • High Confidence Systems!

  16. Intelligent Fault Diagnosis and Prognosis for Engineering Systems

More Related