This paper concerns the distributed state estimation-based security control issue for Internet-of-Things (IoT)-enabled wireless power transfer (WPT) system subject to interchange attacks. The WPT system is first modeled using a state-space framework, and then the IoT elements including Web-enabled smart sensors are considered to obtain measurements for state estimation and control purpose. Additionally, a Bernoulli distribution-based random variable with known probability is introduced to characterize randomly occurring interchange attacks in output measurements. Using Lyapunov theory and stochastic analysis technique, a set of sufficient conditions is established in terms of linear matrix inequalities for ensuring convergence of state estimation with reliable and consistent power transfer operations within the described WPT system applications. Furthermore, particle swarm optimization algorithm is used to determine the optimal gain of the state estimation scheme for minimizing mean-squared estimation errors. Finally, numerical simulation is given to illustrate the efficiency and usefulness of the presented control approach.

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.