Intelligent GPS Spoofing Attack Detection in Power Grids

The GPS is vulnerable to GPS spoofing attack (GSA), which leads to disorder in time and position results of the GPS receiver. In power grids, phasor measurement units (PMUs) use GPS to build time-tagged measurements, so they are susceptible to this attack. As a result of this attack, sampling time and phase angle of the PMU measurements change. In this paper, a neural network GPS spoofing detection (NNGSD) with employing PMU data from the dynamic power system is presented to detect GSAs. Numerical results in different conditions show the real-time performance of the proposed detection method

A Linear Parameter Varying Control Approach for DC/DC Converters in All-Electric Boats

Utilization of renewable energies in association with energy storage is increased in different applications such as electrical vehicles (EVs), electric boats (EBs), and smart grids. A robust controller strategy plays a significant role to optimally utilize the energy resources available in a power system. In this paper, a suitable controller for the energy resources of an EB which consists of a 5 kW solar power plant, 5 kW fuel cell, and 2 kW battery package is designed based on the linear parameter varying (LPV) controller design approach. Initially, all component dynamics are augmented, and by exploiting the sector-nonlinearity approach, the LPV representation is derived. Then, the LPV control method determines the suitable gains of the states’ feedbacks to provide the required pulse commands of the boost converters of the energy resources to regulate the DC-link voltage and supply the power of EB loads. Comparing with the state-of-the-art nonlinear control methods, the developed control approach assures the stability of the overall system, as it considers all component dynamics in the design procedure. The real-time simulation results demonstrate the performance of the designed controller in the creation of a constant DC-link voltage

Robust polytopic-LPV body-weight-dependent control of blood glucose in type-1 diabetes

This paper presents a robust H8 polytopic Linear Parameter Varying (LPV) controller to reg- ulate the blood glucose level in type-1 diabetes patients. The suggested approach utilizes an observer-based controller and polytopic inexact gain-scheduling scheme to construct the stabilizing injecting insulin resilient against the external meal and snack disturbance in Silico. To assure the closed-loop stability and prescribed H8 performance, a Quadratic Lyapunov Function (QLF) is used and the stabilization conditions are derived in terms of Linear Matrix Inequalities (LMIs). The conventional minimal Bergman model is improved by considering the effect of body-weight on the glucose-insulin phenomenon and the new body-weight functions are identified based on real data. Then, for the body-weight-dependent Bergman model, a polytopic-LPV model is obtained. Simulations show the advantages of the developed glucose-insulin model and the robustness of the suggested controller in dealing with the effects of a meal for patients with different weights and avoiding hypoglycemia and hyperglycemia disorders.Peer ReviewedPostprint (published version