Optimization-Based Event-Triggered State Estimation Algorithm for IoT-Based Wind Turbine Systems

In this article, the state estimation problem for wind turbine systems (WTSs) is studied by considering the Internet of Things (IoT) framework. Specifically, the WTS is described in the form of a state-space model along with sensors to obtain required state information. Precisely, to discuss the operating condition of the WTSs, multiobjective PSO-based event-triggered state estimation algorithm is developed. Under the event-triggered framework, the state estimator updates sensor measurements in response to specific triggering events determined by time-varying threshold parameter. This approach enhances communication efficiency by reducing the number of transmitted data packets and minimizing battery usage. The simulation results reveal that developed approach can accurately estimate state which converges to the actual state. Precisely, the conditions are developed based on the Lyapunov technique to ensure that the error system to be asymptotically stable. The developed algorithm can be useful in IoT-based WTSs with optimized communication frequency and reduced network traffic. Moreover, the control design is developed for the addressed systems by employing pole-placement technique. Finally, the effectiveness of the proposed estimation algorithm is demonstrated through numerical simulations by achieving optimal utilization of sensors, communication frequency, networks transmission and battery usage.