This document discusses an adaptive drive control system for dynamically controlling the pitch of rotor blades on airborne wind turbines. It uses adaptive fuzzy control with model predictive control capabilities to respond rapidly to wind speed and load changes. This allows the turbine to maintain a predetermined geostationary position without being blown away. The system was simulated using a 45kW permanent magnet synchronous motor, IGBT-based voltage source inverter, and active filters to smooth output and improve power quality of the transmitted RF power.

1. GROUND BREAKING ENERGY CONVERSION TECHNIQUES AND POWER TRANSMISSION
DESIGN CONCEPTS IN ADVANCED AIRBORNE WIND TURBINE TECHNOLOGY
Govindarajan A Chittaranjan
CANWEA 2009 SEPTEMBER 20 – 23, 2009, TORONTO, ONTARIO
ADAPTIVE DRIVE CONTROL FOR DYNAMIC PITCH CONTROL IN AIRBORNE WIND TURBINES WITH TRANSVERSAL AXIS
I I V
METHODOLODY 690 V AC Power Source AC-AC Converter
PMSM
V I
•The system reads reference global position co-ordinates, the ω
wind speeds and the load dynamics Over Current FAULT and Current
correction
Analogue Signal Processor V&I I
&T
Gate Pulse
Feed
Feed
back
back
•Computes & compares with its actual geostationary co-
Wind speed & Load Sensor ADC
Pulse Generator
ordinates to generate the gating pulses for the rapid switching Pitch Position
duty cycle for the motor drive unit Learning Table Reference Table
Adaptive Fuzzy
•The Motor responds at rapidly to dynamically feather the rotor Main Controller with I & ω Speed [ω] Comparator
control
Altitude
Module
blades which places the turbine at a per-determined Air
Torque [T] Comparator
geostationary coordinates. Density
Current [I] comparator
THE FLOW DIAGRAM DIPECTS THE ADAPTIVE DRIVE
GPS Reference GPS Comparator GPS Actual
CONTROL SYSTEM
INTRODUCTION SPECIFICATIONS SIMULATIONS USING PSIM Version 6
• Transversal Axis – Twin Rotor
One of the primary concerns in an airborne wind
turbine without tethers is to stay geostationary without • Helium Impregnated Technologies to keep wind turbine
getting blown away by the wind. To achieve this, the airborne
pitch angle of the rotor blades has to be dynamically
• A positive cost benefit trade-off could be achieved by using
varied at high response rate and speed with bi- ring generators of over 5 MW on each side
directional capabilities. Energy produced from the twin
generators’ is transmitted via RF mode ‫ 781 =ح‬Nm [range : 5 Nm to 187 Nm ]
• Adaptive MPC [Model Predictive Control] with multiple
P = 45 kW [ PMSM: 440 V/ 60 Hz/ 50 kVA]
referencing and learning abilities for a full bridge IGBT based
Due to system non-linearity and high load dynamics it Vd = Vo = 440 V f = 20 kHz
VSI
would be difficult to optimize the parameters of a PMSM: 50 kVA, 440V/60 Hz, η:95% J:0.18,
ω:2300, I:208.8 A
conventional PI controller for extended durations • 3-Phase 45 kW PMSM 2300 rpm rated for 187 Nm for
hence for the same reason this solution is replaced by VSI: IGBT: 1200V, 225A, 2.3V saturation, 85
dynamic feathering of the rotor blades.
a the adaptive neural network and fuzzy control deg C.
Controller: PWM: 20V peak to peak; f=20kHz
system with multiple referencing and learning abilities • The Active Filters to smooth out EMI, output ripple and
to offer a Model Predictive Control [MPC] in the actual DC Link: 880 mF, 440V 60Hz electrolytic
improve the Power Factor
Model. VSC: Full bridge Diode