Biblio

Multi-active bridge (MAB) converter has played an important role in the power conversion of renewable-based smart grids, electrical vehicles, and more/all electrical aircraft. However, the increase of MAB submodules greatly complicates the control architecture. In this regard, the conventional centralized control strategies, which rely on a single controller to process all the information, will be limited by the computation burden. To overcome this issue, this paper proposes a decentralized power management strategy for MAB converter. The switching frequencies of MAB submodules are adaptively regulated based on the submodule local information. Through this effort, flexible electrical power routing can be realized without communications among submodules. The proposed methodology not only relieves the computation burden of MAB control system, but also improves its modularity, flexibility, and expandability. Finally, the experiment results of a three-module MAB converter are presented for verification.

In this paper, a multiple switches open-fault diagnostic method using ANNs (Artificial Neural Networks) for three-phase PWM (Pulse Width Modulation) converters is proposed. When an open-fault occurs on switches in the converter, the stator currents can include dc and harmonic components. Since these abnormal currents cannot be easily cut off by protection circuits, secondary faults can occur in peripherals. Therefore, a method of diagnosing the open-fault is required. For open-faults for single switch and double switches, there are 21 types of fault modes depending on faulty switches. In this paper, these fault modes are localized by using the dc component and THD (Total Harmonics Distortion) in fault currents. For obtaining the dc component and THD in the currents, an ADALINE (Adaptive Linear Neuron) is used. For localizing fault modes, two ANNs are used in series; the 21 fault modes are categorized into six sectors by the first ANN of using the dc components, and then the second ANN localizes fault modes by using both the dc and THDs of the d-q axes current in each sector. Simulations and experiments confirm the validity of the proposed method.

This paper presents the development of a control circuit to enhance the performances of LED lamps. In this direction, a comparison between the luminous intensity of normal LED based lamps and mid-power ones, for both continuous and switching conditions has been made. The already well know control technologies were analyzed and a study was conducted to increase the lighting performances by rising the operating frequency and magnifying the contribution of remanence effect and thus increasing the efficiency of the light source. To achieve this, in the first stage of the project the power and control circuits have been modeled, related to desired parameters and tested in simulation software. In the second stage, the proposed circuit was implemented by functional blocks and in the last stage, tests were made on the circuit and on light sources in order to process the results. The power consumption has been decreased nearly to a half of it and the luminous flux raised with 15% due to overcurrent and remanence effect that we used.

The progress made in terms of controller technologies with the introduction of remotely-accessibility capacity in the digital controllers has opened the door to new cybersecurity threats on the Industrial Control Systems (ICSs). Among them, some aim at damaging the ICS's physical system. In this paper, a corrupted controller emitting a non-legitimate Pulse Width Modulation control signal to an Electro-Mechanical Actuator (EMA) is considered. The attacker's capabilities for accelerating the EMA's aging by inducing Partial Discharges (PDs) are investigated. A simplified model is considered for highlighting the influence of the carrier frequency of the control signal over the amplitude and the repetition of the PDs involved in the EMA's aging.

This work proposes a scheme to detect, isolate and mitigate malicious disruption of electro-mechanical processes in legacy PLCs where each PLC works as a finite state machine (FSM) and goes through predefined states depending on the control flow of the programs and input-output mechanism. The scheme generates a group-signature for a particular state combining the signature shares from each of these PLCs using \$(k,\textbackslashtextbackslash l)\$-threshold signature scheme.If some of them are affected by the malicious code, signature can be verified by k out of l uncorrupted PLCs and can be used to detect the corrupted PLCs and the compromised state. We use OpenPLC software to simulate Legacy PLC system on Raspberry Pi and show İ/O\$ pin configuration attack on digital and pulse width modulation (PWM) pins. We describe the protocol using a small prototype of five instances of legacy PLCs simultaneously running on OpenPLC software. We show that when our proposed protocol is deployed, the aforementioned attacks get successfully detected and the controller takes corrective measures. This work has been developed as a part of the problem statement given in the Cyber Security Awareness Week-2017 competition.

Recently, there has been a pronounced increase of interest in the field of renewable energy. In this area power inverters are crucial building blocks in a segment of energy converters, since they change direct current (DC) to alternating current (AC). Grid connected power inverters should operate in synchronism with the grid voltage. In this paper, the structure of a power system based on adaptive filtering is described. The main purpose of the adaptive filter is to adapt the output signal of the inverter to the corresponding load and/or grid signal. By involving adaptive filtering the response time decreases and quality of power delivery to the load or grid increases. A comparative analysis which relates to power system operation without and with adaptive filtering is given. In addition, the impact of variable impedance of load on quality of delivered power is considered. Results which relates to total harmonic distortion (THD) factor are obtained by Matlab/Simulink software.