Secure and Privacy-Preserving Average Consensus

Average consensus is fundamental for distributed systems since it underpins key functionalities of such systems ranging from distributed information fusion, decision-making, to decentralized control. In order to reach an agreement, existing average consensus algorithms require each agent to exchange explicit state information with its neighbors. This leads to the disclosure of private state information, which is undesirable in cases where privacy is of concern. In this paper, we propose a novel approach that enables secure and privacy-preserving average consensus in a decentralized architecture in the absence of any trusted third-parties. By leveraging homomorphic cryptography, our approach can guarantee consensus to the exact value in a deterministic manner. The proposed approach is light-weight in computation and communication, and applicable to time-varying interaction topology cases. A hardware implementation is presented to demonstrate the capability of our approach.Comment: 7 pages, 4 figures, paper is accepted to CPS-SPC'1

Statisticall Process Control

Tato diplomová práce se zabývá využitím metody SPC v prostředí strojírenské výroby. Práce je koncipována jako návod k zavedení a používání SPC ve výrobě. Důvodem zavedení SPC je snaha o neustálé zlepšování jakosti. Při implementaci samotné metody bylo použito systémového přístupu, aby účinnost nasazení byla co největší. Práce obsahuje tři základní části – teoretickou, návrh postupu řešení a praktickou realizaci.This dissertation deals with utilisation of the method SPC in the field of engineering production. The work is outlined as instructions for introduction and usage of SPC in production. The reason for introduction of SPC is the effort to improve the quality constantly. The systematic approach was used for implementation of the very method so that the efficiency of the introduction is as high as possible. The dissertation contains three fundamental parts – theoretical part, suggestion of the process of the solution and practical implementation.

Statistical process control implementation in the food industry: A systematic review and implications for future research

This study is to illustrate a systematic review application in investigating common issues emerging from Statistical Process Control (SPC) implementation in the food industry. A total of 34 journal articles were rigorously selected from four databases and reviewed. The most common themes emerge in SPC implementation in the food industry is the benefits while the remaining themes are motivation, barriers and critical success factors (CSF). This review found that the evidence of SPC implementation in the food industry is beneficial; however, a lack of both awareness and guidelines relating to SPC implementation in the food industry has resulted in a slow adoption. This systematic review concluded that there is a crucial need for further research into the SPC deployment aspect addressing how to deploy SPC in the food industry in a systematic manner

LMI-based control design to enhance robustness of synchronous power controller

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Synchronous power controller (SPC) has emerged as a suitable technique to equip grid-connected inverters with grid supporting functionalities such as inertial emulation and frequency/voltage support by mimicking the behavior of synchronous machines. Although the feasibility of the SPC has been experimentally verified under various operating conditions, parameter tuning for the SPC to ensure a stable inverter system has not been adequately addressed in the literature. To fill this gap, this paper presents a robust control design for the SPC to ensure its stable operation under the grid impedance variation. The proposed design procedure consists of system modelling and robust optimal parameter selection by using linear matrix inequality approach. The effectiveness of the proposed control design is proven by means of simulations and experiments.Peer ReviewedPostprint (author's final draft

Multicast Multigroup Beamforming under Per-antenna Power Constraints

Linear precoding exploits the spatial degrees of freedom offered by multi-antenna transmitters to serve multiple users over the same frequency resources. The present work focuses on simultaneously serving multiple groups of users, each with its own channel, by transmitting a stream of common symbols to each group. This scenario is known as physical layer multicasting to multiple co-channel groups. Extending the current state of the art in multigroup multicasting, the practical constraint of a maximum permitted power level radiated by each antenna is tackled herein. The considered per antenna power constrained system is optimized in a maximum fairness sense. In other words, the optimization aims at favoring the worst user by maximizing the minimum rate. This Max-Min Fair criterion is imperative in multicast systems, where the performance of all the receivers listening to the same multicast is dictated by the worst rate in the group. An analytic framework to tackle the Max-Min Fair multigroup multicasting scenario under per antenna power constraints is therefore derived. Numerical results display the accuracy of the proposed solution and provide insights to the performance of a per antenna power constrained system.Comment: Presented in IEEE ICC 2014, Sydney, AUS. arXiv admin note: substantial text overlap with arXiv:1406.755

Output feedback stable stochastic predictive control with hard control constraints

We present a stochastic predictive controller for discrete time linear time invariant systems under incomplete state information. Our approach is based on a suitable choice of control policies, stability constraints, and employment of a Kalman filter to estimate the states of the system from incomplete and corrupt observations. We demonstrate that this approach yields a computationally tractable problem that should be solved online periodically, and that the resulting closed loop system is mean-square bounded for any positive bound on the control actions. Our results allow one to tackle the largest class of linear time invariant systems known to be amenable to stochastic stabilization under bounded control actions via output feedback stochastic predictive control

Religious education in Serbia

Grußwort zur Eröffnung des Centrums für Religiöse Studien (Wolf D. Ahmed Aries) 27 Festvortrag Kinder Abrahams. Zur Möglichkeit und Notwendigkeit eines Miteinander von Juden, Christen und Muslimen (Karl-Josef Kuschet) 33 Beiträge ..