Predictive functional control of power kites for high altitude wind energy generation based on hybrid neural network

The power kite is a kind of high altitude wind energy (HAWE), which has received an increasing attention in the last decade. The unique feature of the kite-based system is its structural simplicity coupled with the complexity in its modeling and control. Since the system is open-loop unstable, it is difficult to model and it subjects to significant external disturbances during operation. To address these challenges, nonlinear predictive functional controller (PFC) is presented in this paper. Firstly, a predictive model is established for the power kite using hybrid neural network, and then the PFC principles are applied for its controller design. With the neural network structure, the PFC integrates on-line identification, learning mechanism and predictive controller. A closed-loop control system is developed and implemented to improve the performance of the power kite. The effectiveness of the proposed approach has been illustrated by numerical simulation tests.