Resilience-oriented control and communication framework for cyber-physical microgrids

Climate change drives the energy supply transition from traditional fossil fuel-based power generation to renewable energy resources. This transition has been widely recognised as one of the most significant developing pathways promoting the decarbonisation process toward a zero-carbon and sustainable society. Rapidly developing renewables gradually dominate energy systems and promote the current energy supply system towards decentralisation and digitisation. The manifestation of decentralisation is at massive dispatchable energy resources, while the digitisation features strong cohesion and coherence between electrical power technologies and information and communication technologies (ICT). Massive dispatchable physical devices and cyber components are interdependent and coupled tightly as a cyber-physical energy supply system, while this cyber-physical energy supply system currently faces an increase of extreme weather (e.g., earthquake, flooding) and cyber-contingencies (e.g., cyberattacks) in the frequency, intensity, and duration. Hence, one major challenge is to find an appropriate cyber-physical solution to accommodate increasing renewables while enhancing power supply resilience. The main focus of this thesis is to blend centralised and decentralised frameworks to propose a collaboratively centralised-and-decentralised resilient control framework for energy systems i.e., networked microgrids (MGs) that can operate optimally in the normal condition while can mitigate simultaneous cyber-physical contingencies in the extreme condition. To achieve this, we investigate the concept of "cyber-physical resilience" including four phases, namely prevention/upgrade, resistance, adaption/mitigation, and recovery. Throughout these stages, we tackle different cyber-physical challenges under the concept of microgrid ranging from a centralised-to-decentralised transitional control framework coping with cyber-physical out of service, a cyber-resilient distributed control methodology for networked MGs, a UAV assisted post-contingency cyber-physical service restoration, to a fast-convergent distributed dynamic state estimation algorithm for a class of interconnected systems.Open Acces

Analysis, filtering, and control for Takagi-Sugeno fuzzy models in networked systems

Copyright © 2015 Sunjie Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The fuzzy logic theory has been proven to be effective in dealing with various nonlinear systems and has a great success in industry applications. Among different kinds of models for fuzzy systems, the so-called Takagi-Sugeno (T-S) fuzzy model has been quite popular due to its convenient and simple dynamic structure as well as its capability of approximating any smooth nonlinear function to any specified accuracy within any compact set. In terms of such a model, the performance analysis and the design of controllers and filters play important roles in the research of fuzzy systems. In this paper, we aim to survey some recent advances on the T-S fuzzy control and filtering problems with various network-induced phenomena. The network-induced phenomena under consideration mainly include communication delays, packet dropouts, signal quantization, and randomly occurring uncertainties (ROUs). With such network-induced phenomena, the developments on T-S fuzzy control and filtering issues are reviewed in detail. In addition, some latest results on this topic are highlighted. In the end, conclusions are drawn and some possible future research directions are pointed out.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 11301118 and 61174136, the Natural Science Foundation of Jiangsu Province of China under Grant BK20130017, the Fundamental Research Funds for the Central Universities of China under Grant CUSF-DH-D-2013061, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

A Resilient Control Approach to Secure Cyber Physical Systems (CPS) with an Application on Connected Vehicles

The objective of this dissertation is to develop a resilient control approach to secure Cyber Physical Systems (CPS) against cyber-attacks, network failures and potential physical faults. Despite being potentially beneficial in several aspects, the connectivity in CPSs poses a set of specific challenges from safety and reliability standpoint. The first challenge arises from unreliable communication network which affects the control/management of overall system. Second, faulty sensors and actuators can degrade the performance of CPS and send wrong information to the controller or other subsystems of the CPS. Finally, CPSs are vulnerable to cyber-attacks which can potentially lead to dangerous scenarios by affecting the information transmitted among various components of CPSs. Hence, a resilient control approach is proposed to address these challenges. The control approach consists of three main parts:(1) Physical fault diagnostics: This part makes sure the CPS works normally while there is no cyber-attacks/ network failure in the communication network; (2) Cyber-attack/failure resilient strategy: This part consists of a resilient strategy for specific cyber-attacks to compensate for their malicious effects ; (3) Decision making algorithm: The decision making block identifies the specific existing cyber-attacks/ network failure in the system and deploys corresponding control strategy to minimize the effect of abnormality in the system performance. In this dissertation, we consider a platoon of connected vehicle system under Co-operative Adaptive Cruise Control (CACC) strategy as a CPS and develop a resilient control approach to address the aforementioned challenges. The first part of this dissertation investigates fault diagnostics of connected vehicles assuming ideal communication network. Very few works address the real-time diagnostics problem in connected vehicles. This study models the effect of different faults in sensors and actuators, and also develops fault diagnosis scheme for detectable and identifiable faults. The proposed diagnostics scheme is based on sliding model observers to detect, isolate and estimate faults in the sensors and actuators. One of the main advantages of sliding model approach lies in applicability to nonlinear systems. Therefore, the proposed method can be extended for other nonlinear cyber physical systems as well. The second part of the proposed research deals with developing strategies to maintain performance of cyber-physical systems close to the normal, in the presence of common cyber-attacks and network failures. Specifically, the behavior of Dedicated Short-Range Communication (DSRC) network is analyzed under cyber-attacks and failures including packet dropping, Denial of Service (DOS) attack and false data injection attack. To start with, packet dropping in network communication is modeled by Bernoulli random variable. Then an observer based modifying algorithm is proposed to modify the existing CACC strategy against the effect of packet dropping phenomena. In contrast to the existing works on state estimation over imperfect communication network in CPS which mainly use either holding previous received data or Kalman filter with intermittent observation, a combination of these two approaches is used to construct the missing data over packet dropping phenomena. Furthermore, an observer based fault diagnostics based on sliding mode approach is proposed to detect, isolate and estimate sensor faults in connected vehicles platoon. Next, Denial of Service (DoS) attack is considered on the communication network. The effect of DoS attack is modeled as an unknown stochastic delay in data delivery in the communication network. Then an observer based approach is proposed to estimate the real data from the delayed measured data over the network. A novel approach based on LMI theory is presented to design observer and estimate the states of the system via delayed measurements. Next, we explore and alternative approach by modeling DoS with unknown constant time delay and propose an adaptive observer to estimate the delay. Furthermore, we study the effects of system uncertainties on the DoS algorithm. In the third algorithm, we considered a general CPS with a saturated DoS attack modeled with constant unknown delay. In this part, we modeled the DoS via a PDE and developed a PDE based observer to estimate the delay as well as states of the system while the only available measurements are delayed. Furthermore, as the last cyber-attack of the second part of the dissertation, we consider false data injection attack as the fake vehicle identity in the platoon of vehicles. In this part, we develop a novel PDE-based modeling strategy for the platoon of vehicles equipped with CACC. Moreover, we propose a PDE based observer to detect and isolate the location of the false data injection attack injected into the platoon as fake identity. Finally, the third part of the dissertation deals with the ongoing works on an optimum decision making strategy formulated via Model Predictive Control (MPC). The decision making block is developed to choose the optimum strategy among available strategies designed in the second part of the dissertation

Design and Implementation of Attack-Resilient Cyber-Physical Systems

Recent years have witnessed a significant increase in the number of security-related incidents in control systems. These include high-profile attacks in a wide range of application domains, from attacks on critical infrastructure, as in the case of the Maroochy Water breach [1], and industrial systems (such as the StuxNet virus attack on an industrial supervisory control and data acquisition system [2], [3] and the German Steel Mill cyberattack [4], [5]), to attacks on modern vehicles [6]-[8]. Even high-assurance military systems were shown to be vulnerable to attacks, as illustrated in the highly publicized downing of the RQ-170 Sentinel U.S. drone [9]-[11]. These incidents have greatly raised awareness of the need for security in cyberphysical systems (CPSs), which feature tight coupling of computation and communication substrates with sensing and actuation components. However, the complexity and heterogeneity of this next generation of safety-critical, networked, and embedded control systems have challenged the existing design methods in which security is usually consider as an afterthought

Error-resilient performance of Dirac video codec over packet-erasure channel

Video transmission over the wireless or wired network requires error-resilient mechanism since compressed video bitstreams are sensitive to transmission errors because of the use of predictive coding and variable length coding. This paper investigates the performance of a simple and low complexity error-resilient coding scheme which combines source and channel coding to protect compressed bitstream of wavelet-based Dirac video codec in the packet-erasure channel. By partitioning the wavelet transform coefficients of the motion-compensated residual frame into groups and independently processing each group using arithmetic and Forward Error Correction (FEC) coding, Dirac could achieves the robustness to transmission errors by giving the video quality which is gracefully decreasing over a range of packet loss rates up to 30% when compared with conventional FEC only methods. Simulation results also show that the proposed scheme using multiple partitions can achieve up to 10 dB PSNR gain over its existing un-partitioned format. This paper also investigates the error-resilient performance of the proposed scheme in comparison with H.264 over packet-erasure channel

Detection of replay attacks in cyber-physical systems using a frequency-based signature

This paper proposes a frequency-based approach for the detection of replay attacks affecting cyber-physical systems (CPS). In particular, the method employs a sinusoidal signal with a time-varying frequency (authentication signal) into the closed-loop system and checks whether the time profile of the frequency components in the output signal are compatible with the authentication signal or not. In order to carry out this target, the couplings between inputs and outputs are eliminated using a dynamic decoupling technique based on vector fitting. In this way, a signature introduced on a specific input channel will affect only the output that is selected to be associated with that input, which is a property that can be exploited to determine which channels are being affected. A bank of band-pass filters is used to generate signals whose energies can be compared to reconstruct an estimation of the time-varying frequency profile. By matching the known frequency profile with its estimation, the detector can provide the information about whether a replay attack is being carried out or not. The design of the signal generator and the detector are thoroughly discussed, and an example based on a quadruple-tank process is used to show the application and effectiveness of the proposed method.Peer ReviewedPostprint (author's final draft

Distributed filtering of networked dynamic systems with non-gaussian noises over sensor networks: A survey

summary:Sensor networks are regarded as a promising technology in the field of information perception and processing owing to the ease of deployment, cost-effectiveness, flexibility, as well as reliability. The information exchange among sensors inevitably suffers from various network-induced phenomena caused by the limited resource utilization and complex application scenarios, and thus is required to be governed by suitable resource-saving communication mechanisms. It is also noteworthy that noises in system dynamics and sensor measurements are ubiquitous and in general unknown but can be bounded, rather than follow specific Gaussian distributions as assumed in Kalman-type filtering. Particular attention of this paper is paid to a survey of recent advances in distributed filtering of networked dynamic systems with non-Gaussian noises over sensor networks. First, two types of widely employed structures of distributed filters are reviewed, the corresponding analysis is systematically addressed, and some interesting results are provided. The inherent purpose of adding consensus terms into the distributed filters is profoundly disclosed. Then, some representative models characterizing various network-induced phenomena are reviewed and their corresponding analytical strategies are exhibited in detail. Furthermore, recent results on distributed filtering with non-Gaussian noises are sorted out in accordance with different network-induced phenomena and system models. Another emphasis is laid on recent developments of distributed filtering with various communication scheduling, which are summarized based on the inherent characteristics of their dynamic behavior associated with mathematical models. Finally, the state-of-the-art of distributed filtering and challenging issues, ranging from scalability, security to applications, are raised to guide possible future research