Iterative learning control of wind turbine smart rotors with pressure sensors

Improving the aerodynamic effectiveness and hence energy production of wind turbines is of critical importance and there is currently research into to the inclusion of smart devices in rotor blades in conjunction with collective and individual pitch control. The main objective is to reduce fatigue loads which have periodic and non-periodic components. This paper gives further results on the use of iterative learning control in this application area based on first constructing a simple but realistic computational fluid dynamics model to represent flow past an airfoil. The new results are based on the use of pressure sensors to estimate the lift.