Event‐Triggered Lyapunov‐Based Model Predictive Control for Wind Energy Systems With Measurement Delays

Measurement delays, nonlinearities and external uncertainties cannot be avoided for wind energy system under complex working environment in practical. This article proposes an event‐triggered Lyapunov‐based model predictive control (LMPC) framework for wind energy systems. To better reflect the practical environment, a nonlinear system model is established for explicitly incorporating measurement delays and external uncertainties. An LMPC method is designed for wind energy system with Lyapunov constraints to improve the control performance. A triggering scheme is proposed for LMPC to reduce optimization computation time in controller design, which makes the proposed LMPC more applicable. The closed‐loop stability is demonstrated for the proposed event‐triggered LMPC with measurement delays. Finally, simulation experiments are conducted on a 5‐MW wind energy system to validate and illustrate the effectiveness of the proposed LMPC approach.