Self-Designing Control Systems for Piloted and Uninhabited Aerial Vehicles

Abstract

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the wne for rev the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate reducing this burden to Department of Defense, Washington Headquarters Services. Directorate for Information Operations ar VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. AFRL-SR-BL-TR-01- PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Department of Electrical Engineering University of Utah 50 S Central Campus Dr Rm 3280Salt Lake City, UT 84112-9206 PERFORMING ORGANIZATION REPORT NUMBER SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES)Dr Marc Jacobs AFOSR/NM 801 North Randolph Street, Room 732 Arlington, VA 22203-1977 SPONSOR/MONITOR'S ACRONYM(S)AIR FORC^ OFFICE OF SCIENTIFIC RESEARCH (AFOSR) NOTICE 0 -iH^:^Mi*i6Wfrkiä^,rifaHhWjHTHASBEft REViCTTW WBR^PPROVEO FOR PUBUC RELEASE IAWAFR I19M?> ni,STRIRIJTIONISUNIIMITFn DISTRIBUTION / AVAILABILITY STATEMENTApproved for public release; distribution unlimited. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes. SUPPLEMENTARY NOTES " " ~*~ "The views and conclusions contained in the report are those of the author and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Air Force Offhe of Scientific Research or the U.S. Government. ABSTRACT ~~ "The main advantage of self-designing flight control systems is their abi.ny to optimize performance automatically, resulting in a substantial reduction of the cost and time needed for control law development. Self-designing control systems also reconfigure automatically after failures and damages, yielding greater chances of survival in dangerous conditions. A self-designing nonlinear autopilot was developed to interface with the high-level path planning of a UAV. The control algorithm is distinct from conventional autopilots in that it is not based on a known, linearized model of the aircraft. Instead, the algorithm compensates for nonlinear dynamic effects and adjusts its parameters automatically, exploiting the reconfiguration capabilities of an inner control loop designed using adaptive methods. A new control allocation algorithm was also developed, based on the direct allocation method of Durham. A special representation using spherical coordinates was used to speed-up the computations that must be performed at a high sampling rate. The direct allocation method was also extended to a class of systems that had previously been excluded, namely those for which some independent control surfaces produce linearly dependent moments. Finally, fast algorithms for optimal control allocation were developed based on linear programming techniques. It was observed that significant improvements i...