Proportional integral observer-based resilient control for inductively coupled power transfer system using particle swarm optimization

This research study centers on stochastic stabilization for inductively coupled power transfer systems in the midst of stochastic disturbances by means of resilient control and particle swarm optimization strategy. Precisely, a particle swarm optimization algorithm has been put in place to lower the cost function and boost the system's overall efficiency. Subsequently, the proportional integral observer is framed with the intent to estimate the states of the considered model. In this instance, the output of the system is quantized before it gets fed into the observer system via the logarithmic quantizer owing to the limited capacity of the communication route. From there on, with the aid of estimated states, the proportional integral observer-based resilient control is configured, facilitating the intended finite-time stochastic stabilization of inductively coupled power transfer systems. Furthermore, the resiliency of the controller is enhanced by including perturbations in the controller gain. Moreover, by using Lyapunov stability theory and Ito's formula, linear matrix inequality-based conditions are established, which act as sufficient requirements for ascertaining the outcomes that are sought after. In the end, the presented simulation outcomes demonstrate the viability of the established theoretical outcomes and control scheme.