Development of Knowledge-Based Software for UAV Autopilot Design George Tarrant Director CLOSED LOOP SYSTEMS
Health Warning Autopilot design is a technical subject. In this paper, I have tried to translate the technicalities into readily understandable terms but I regret that sometimes it has been necessary to stray into technical territory to make my points. george.tarrant@btconnect.com
Presentation Outline Off-the-shelf autopilot features Currently suggested autopilot set-up process Integration of new autopilot set-up process Estimation of aerodynamic derivatives Knowledge-based autopilot design Design process numerical illustration Software features and benefits
UAS functional blocks GPS AUTOPILOT Control laws Gyros Accelerometers AIRCRAFT Propulsion Servos Airframe PIC/CIC IMAGING SENSOR MISSION CONTROL Uplink commands image/data capture mission simulator
Off-the-shelf autopilot tuning Supplied with control law gains matched to R/C trainer User responsible for matching gains to host aircraft Trial-and-error process mission simulator actual flight Continues until observed aircraft response deemed acceptable Can deliver reasonable response but not really satisfactory time-consuming reliant on perceptual and analytical abilities of the user fails to address wind effects Potentially some risk to timescale, cost and/or performance
Integration of new autopilot set-up process Default autopilot gains Trial and error tuning New aero (AVL) MISSION SIMULATOR RESPONSE TESTING ADJUST AUTOPILOT GAINS Baseline servo/ inertial sensor models (AUTOPILOT) Alternative servo/ inertial sensor models New aero (doublets) KNOWLEDGE-BASED AUTOPILOT DESIGN SOFTWARE FLIGHT TEST
Estimation of aerodynamic derivatives (1) Parameter adjustment algorithm Parameter adjustments Iterative loop Doublet input Parametric model of aircraft response Model response Summation of squared error Aircraft Datalog Actual response
Elevator fine servo (rads) Gyro outputs (rads/sec) Elevator demand (rads) 0.3 Estimation of aerodynamic derivatives (2) 0.2 0.1 Doublet 5 Doublet 7 Doublet 8 0 250 300 350 400 450 500 Time (sec) -0.1 Doublet 6-0.2 0.02-0.3 0.01 0 0 0.5 1 1.5 2 2.5 3-0.01-0.02-0.4-0.03-0.04-0.05-0.06-0.07 Time (sec) 0.6 0.5 0.4 0.3 0.2 0.1 0 Actual gyro output Model gyro output 0 0.5 1 1.5 2 2.5 3-0.1-0.08 Time (sec) -0.2 Time (sec)
Hierarchy of autopilot loops Airspeed Throttle from airspeed throttle Altitude Pitch from airspeed Pitch from altitude pitch 0 Elevator from pitch Rudder from Yacc elevator rudder Aircraft Dynamics airspeed pitch roll Aircraft Kinematic s altitude Heading Roll from heading roll Aileron from roll aileron heading PRIMARY STABILITY LOOPS NAVIGATION LOOPS
Elevator from pitch primary stability loop Wind disturbance PID shaping Elevator servo Pitch demand P + I Airframe pitch dynamics Pitch rate Actual pitch angle Estimated pitch angle ( D term) K d Pitch damper (Attitude computer) Update rate Pitch rate gyro
Autopilot Design Strategy K d Elevator servo Rate Gyro Airframe P+I 0 Attitude computer Pitch Damper Navigation Loops Pitch damper Primary stability loop Navigation loops Rejection of wind disturbances servo bandwidth gyro bandwidth processor update rate airframe stability Response to the demand limits on elevator travel rate gyro FSD PID gains f( 0 )
Pitch rate response (rads/sec) Pitch damper responses 0.1 0.05 Wind disturbance 1 m/sec step 0-0.05 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2-0.1-0.15-0.2 1/500th sec Indicative blur limits (Camera resolution 15 cm at 600m; f = 50 mm) -0.25-0.3-0.35-0.4 1/1000th sec Time (sec) Bare airframe Nominal autopilot + 3 Hz servo Faster autopilot + 3 Hz servo Faster autopilot + 6 Hz servo Faster autopilot + 10 Hz servo
Elevator deflection (degrees) Body pitch rate (deg/sec) Responses to a pitch attitude command of 20 120 100 80 60 40 omega0=0.5 r/sec omega0=1.0 r/sec omega0=1.5 r/sec Body pitch rate response 20 0 0 0.5 1 1.5 2 2.5 3-20 Time (sec) 5 0 0 0.5 1 1.5 2 2.5 3-5 Elevator response -10-15 omega0=0.5 r/sec omega0=1.0 r/sec omega0=1.5 r/sec -20-25 -30 Time (sec)
Software features and benefits Relevant to a large class of autopilots using PID control Integrates seamlessly with existing autopilot set-up Has autopilot knowhow embedded Leads the user by the hand through the design process Computationally very quick Radically reduces autopilot set-up time and cost Provides near-optimum performance