Real-Time Application of Iterative Feedforward Learning Control for Improving Already Built-in Flight Controllers

Combining feedforward controllers with feedback controllers improves control performance and lowers tracking error. The paper proposes and practically analyzes an intelligent feedforward regulator known as iterative learning control for improving the performance of already built in flight controllers. As the proposed method doesn’t use the mathematical model of the system to design the controller, it independent from the effects of system parameters variations. Real-time results using a quadrotor system show that the proposed controller significantly reduces the tracking error relative to LQR controller. Additionally, it has been shown how straightforward it is to add the proposed feedforward term to an already built-in commercial flight controller.