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Dynamical Systems 2015 |
Research into dynamical systems cited here focuses on non-linear and chaotic dynamical systems and in proving abstractions of dynamical systems through numerical simulations. Many of the applications studied are cyber-physical systems and are relevant to the Science of Security hard problems of resiliency, predictive metrics, and composability. These works were presented in 2015.
R. K. Yedavalli, “Security and Vulnerability in the Stabilization of Networks of Controlled Dynamical Systems via Robustness Framework,” 2015 American Control Conference (ACC), Chicago, IL, 2015, pp. 5396-5401. doi: 10.1109/ACC.2015.7172183
Abstract: This paper addresses the issues of security and vulnerability of links in the stabilization of networked control systems from robustness viewpoint. As is done in recent research, we view network security as a robustness issue. However, in this paper we shed considerable new insight into this topic and offer a new and differing perspective. We argue that `robustness' aspect is a common theme related to both vulnerability and security. This paper puts forth the viewpoint that vulnerability of a networked system is a manifestation of the combination of two types of robustness, namely ‘qualitative robustness’ and ‘quantitative robustness’. In other words, the entire robustness concept is treated as a combination of qualitative robustness and quantitative robustness, wherein qualitative robustness is linked to the system’s nature of interactions and interconnections i.e. system’s structure while quantitative robustness is linked to the system dynamics. Put it another way, qualitative robustness is independent of magnitudes and depends only on the signs of the system dynamics matrix whereas quantitative robustness is purely a function of the quantitative information (both magnitudes and signs) of the entries of the system dynamics matrix. In that sense, these two concepts are inter-related, each influencing and complementing the other. Applying these notions to the networked control systems represented by ‘dynamical structure functions’, it is shown that any specific dynamical structure function originated by a state space represenation, is a function of both qualitative and quantitative robustness. In other words, vulnerability of links in that network is determined by both the signs and magnitudes of that state space matrix of that dynamical structure function. Thus the notion in the recent literature that `vulnerability depends on the system structure, not the dynamics and the robustness, which depends on the dynamics, and not on the system structure' is disput- d and clear justification for our viewpoint is provided by newly introduced notions of ‘qualitative robustness’ and ‘quantitative robustness’. This paper then presents few specific dynamical structure functions that possess a large number of non-vulnerable links which is desirable for a secure network. The proposed concepts are illustrated with many useful examples.
Keywords: matrix algebra; networked control systems; robust control; security; controlled dynamical systems; dynamical structure functions; link security; link vulnerability; network security; networked control system stabilization; qualitative robustness; quantitative robustness; robustness framework; state space matrix; state space represenation; system dynamics; Indexes; Jacobian matrices; Robustness; Security; Stability criteria; Transfer functions (ID#: 16-10196)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7172183&isnumber=7170700
Yingjun Yuan, Zhitao Huang, Fenghua Wang and Xiang Wang, “Radio Specific Emitter Identification Based on Nonlinear Characteristics of Signal,” Communications and Networking (BlackSeaCom), 2015 IEEE International Black Sea Conference on, Constanta, 2015, pp. 77-81. doi: 10.1109/BlackSeaCom.2015.7185090
Abstract: Radio Specific Emitter Identification (SEI) is the technique which identifies the individual radio emitter based on the received signals’ specific properties called signals’ Radio Frequency Fingerprint (RFF). SEI is very significant for improving the security of wireless networks. A novel SEI method which treats the emitter as a nonlinear dynamical system is proposed in this paper. The method works based on the signal’s nonlinear characteristics which result from the unintentional and unavoidable physical-layer imperfections. The reconstructed phase space (RPS) is used as the tool for analyzing the nonlinearity. The entire characteristics of RPS and state changes characteristics of points in RPS are extracted to form RFF. To evaluate the availability of the RFF, the signals from four wireless network cards are collected by a signal acquisition system. The proposed RFF’s discrimination capabilities are visually analyzed using the boxplot. The results of visual analysis and classification demonstrate that this method is effective.
Keywords: nonlinear dynamical systems; radio networks; signal reconstruction; telecommunication security; nonlinear dynamical system; nonlinear signal characteristics; phase space reconstruction; radio specific emitter identification; signal nonlinear characteristics; wireless network security; Conferences; Feature extraction; Fingerprint recognition; Nonlinear dynamical systems; Transient analysis; Visualization; Wireless networks; Specific emitter identification; nonlinearity; phase space; radio frequency fingerprint (ID#: 16-10197)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7185090&isnumber=7185069
J. Wang, Y. Wang, X. Wen, T. Yang and Q. Ding, “The Simulation Research and NIST Test of Binary Quantification Methods for the Typical Chaos,” 2015 Third International Conference on Robot, Vision and Signal Processing (RVSP), Kaohsiung, 2015,
pp. 180-184. doi: 10.1109/RVSP.2015.50
Abstract: In this paper, we study into the binary quantification methods of Logistic, Tent and Lorenz three typical chaos, and apply direction quantization, threshold quantization and interval quantization to quantify typical chaos signal respectively. On the basic of studying the standards of NIST test and the test suite of STS, we do a lot of NIST tests and analysis on the three typical chaos sequence to find the best quantification method for the three typical chaos, and study the impact of the system parameters, the initial value and the length of sequence on the digital chaotic sequence, and achieve better chaotic sequence in randomness, which provide some theoretical guidance to the digital secure communication.
Keywords: chaotic communication; quantisation (signal); NIST test; binary quantification methods; chaos; chaotic sequence; digital chaotic sequence; direction quantization; quantification method; threshold quantization; Chaotic communication; Logistics; NIST; Nonlinear dynamical systems; Quantization (signal); Security; binary quantification; digital secure communication (ID#: 16-10198)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7399174&isnumber=7398743
C. Luo and D. Zeng, “Multivariate Embedding Based Causality Detection with Short Time Series,” Intelligence and Security Informatics (ISI), 2015 IEEE International Conference on, Baltimore, MD, 2015, pp. 138-140. doi: 10.1109/ISI.2015.7165954
Abstract: Existing causal inference methods for social media usually rely on limited explicit causal context, preassume certain user interaction model, or neglect the nonlinear nature of social interaction, which could lead to bias estimations of causality. Besides, they often require sufficiently long time series to achieve reasonable results. Here we propose to take advantage of multivariate embedding to perform causality detection in social media. Experimental results show the efficacy of the proposed approach in causality detection and user behavior prediction in social media.
Keywords: causality; inference mechanisms; social networking (online); time series; bias estimations; causal inference methods; multivariate embedding based causality detection; social interaction; social media; user behavior prediction; user interaction model; Manifolds; Media; Neural networks; Nonlinear dynamical systems; Social network services; Time series analysis; Training; causality detection; multivariate embedding; nonlinear dynamic system; user influence (ID#: 16-10199)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7165954&isnumber=7165923
C. Lee, H. Shim and Y. Eun, “Secure and Robust State Estimation Under Sensor Attacks, Measurement Noises, and Process Disturbances: Observer-Based Combinatorial Approach,” Control Conference (ECC), 2015 European, Linz, 2015, pp. 1872-1877. doi: 10.1109/ECC.2015.7330811
Abstract: This paper presents a secure and robust state estimation scheme for continuous-time linear dynamical systems. The method is secure in that it correctly estimates the states under sensor attacks by exploiting sensing redundancy, and it is robust in that it guarantees a bounded estimation error despite measurement noises and process disturbances. In this method, an individual Luenberger observer (of possibly smaller size) is designed from each sensor. Then, the state estimates from each of the observers are combined through a scheme motivated by error correction techniques, which results in estimation resiliency against sensor attacks under a mild condition on the system observability. Moreover, in the state estimates combining stage, our method reduces the search space of a minimization problem to a finite set, which substantially reduces the required computational effort.
Keywords: continuous time systems; error correction; linear systems; observers; redundancy; robust control; security; Luenberger observer; bounded estimation error; continuous-time linear dynamical system; error correction technique; observer-based combinatorial approach; robust state estimation; search space; secure state estimation; sensor attack; Indexes; Minimization; Noise measurement; Observers; Redundancy; Robustness (ID#: 16-10200)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7330811&isnumber=7330515
D. Palma, P. L. Montessoro, G. Giordano and F. Blanchini, “A Dynamic Algorithm for Palmprint Recognition,” Communications and Network Security (CNS), 2015 IEEE Conference on, Florence, 2015, pp. 659-662. doi: 10.1109/CNS.2015.7346883
Abstract: Most of the existing techniques for palmprint recognition are based on metrics that evaluate the distance between a pair of features. These metrics are typically based on static functions. In this paper we propose a new technique for palmprint recognition based on a dynamical system approach, focusing on preliminary experimental results. The essential idea is that the procedure iteratively eliminates points in both images to be compared which do not have enough close neighboring points in the image itself and in the comparison image. As a result of the iteration, in each image the surviving points are those having enough neighboring points in the comparison image. Our preliminary experimental results show that the proposed dynamic algorithm is competitive and slightly outperforms some state-of-the-art methods by achieving a higher genuine acceptance rate.
Keywords: palmprint recognition; biometric systems; dynamic algorithm; dynamical system approach; iteration; Biometrics (access control); Databases; Feature extraction; Heuristic algorithms; Security; Yttrium (ID#: 16-10201)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7346883&isnumber=7346791
S. W. Neville, M. Elgamal and Z. Nikdel, “Robust Adversarial Learning and Invariant Measures,” Communications, Computers and Signal Processing (PACRIM), 2015 IEEE Pacific Rim Conference on, Victoria, BC, 2015, pp. 529-535. doi: 10.1109/PACRIM.2015.7334893
Abstract: A number of open cyber-security challenges are arising due to the rapidly evolving scale, complexity, and heterogeneity of modern IT systems and networks. The ease with which copious volumes of operational data can be collected from such systems has produced a strong interest in the use of machine learning (ML) for cyber-security, provided that ML can itself be made sufficiently immune to attack. Adversarial learning (AL) is the domain focusing on such issues and an arising AL theme is the need to ensure that ML solutions make use of robust input measurement features (i.e., the data sets used for ML training must themselves be robust against adversarial influences). This observation leads to further open questions, including: “What formally denotes sufficient robustness?”, “Must robust features necessarily exist for all IT systems?”, “Do robust features necessarily provide complete coverage of the attack space?”, etc. This work shows that these (and other) open AL questions can be usefully re-cast in terms of the classical dynamical system’s problem of needing to focus analyses on a system’s invariant measures. This re-casting is useful as a large body of mature dynamical systems theory exists concerning invariant measures which can then be applied to cyber-security. To our knowledge this the first work to identify and highlight this potentially useful cross-domain linkage.
Keywords: learning (artificial intelligence); security of data; ML training; adversarial learning; cross-domain linkage; cyber-security; machine learning; Complexity theory; Computer security; Extraterrestrial measurements; Focusing; Robustness; Sensors
(ID#: 16-10202)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7334893&isnumber=7334793
H. A. Kingravi, H. Maske and G. Chowdhary, “Kernel Controllers: A Systems-Theoretic Approach for Data-Driven Modeling and Control of Spatiotemporally Evolving Processes,” 2015 54th IEEE Conference on Decision and Control (CDC), Osaka, 2015, pp. 7365-7370. doi: 10.1109/CDC.2015.7403382
Abstract: We consider the problem of modeling, estimating, and controlling the latent state of a spatiotemporally evolving continuous function using very few sensor measurements and actuator locations. Our solution to the problem consists of two parts: a predictive model of functional evolution, and feedback based estimator and controllers that can robustly recover the state of the model and drive it to a desired function. We show that layering a dynamical systems prior over temporal evolution of weights of a kernel model is a valid approach to spatiotemporal modeling that leads to systems theoretic, control-usable, predictive models. We provide sufficient conditions on the number of sensors and actuators required to guarantee observability and controllability. The approach is validated on a large real dataset, and in simulation for the control of spatiotemporally evolving function.
Keywords: estimation theory; feedback; predictive control; simulation; system theory; actuator locations; data-driven modeling; feedback based estimator; kernel controllers; predictive model; ; spatiotemporally evolving continuous function; systems-theoretic approach; Dictionaries; High definition video; Hilbert space; Kernel; Mathematical model; Predictive models; Spatiotemporal phenomena (ID#: 16-10203)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7403382&isnumber=7402066
J. Zhang, “An Image Encryption Scheme Based on Cat Map and Hyperchaotic Lorenz System,” Computational Intelligence & Communication Technology (CICT), 2015 IEEE International Conference on, Ghaziabad, 2015, pp. 78-82. doi: 10.1109/CICT.2015.134
Abstract: In recent years, chaos-based image cipher has been widely studied and a growing number of schemes based on permutation-diffusion architecture have been proposed. However, recent studies have indicated that those approaches based on low-dimensional chaotic maps/systems have the drawbacks of small key space and weak security. In this paper, a security improved image cipher which utilizes cat map and hyper chaotic Lorenz system is reported. Compared with ordinary chaotic systems, hyper chaotic systems have more complex dynamical behaviors and number of system variables, which demonstrate a greater potential for constructing a secure cryptosystem. In diffusion stage, a plaintext related key stream generation strategy is introduced, which further improves the security against known/chosen-plaintext attack. Extensive security analysis has been performed on the proposed scheme, including the most important ones like key space analysis, key sensitivity analysis and various statistical analyses, which has demonstrated the satisfactory security of the proposed scheme.
Keywords: cryptography; image processing; statistical analysis; cat map; chaos-based image cipher; complex dynamical behaviors; cryptosystem; hyperchaotic Lorenz system; image encryption scheme; key sensitivity analysis; key space analysis; key stream generation strategy; low-dimensional chaotic maps; permutation-diffusion architecture; security analysis; Chaotic communication; Ciphers; Correlation; Encryption; image cipher; permutation-diffusion (ID#: 16-10204)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7078671&isnumber=7078645
W. Qi et al., “A Dynamic Reactive Power Reserve Optimization Method to Enhance Transient Voltage Stability,” Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2015 IEEE International Conference on, Shenyang, 2015, pp. 1523-1528. doi: 10.1109/CYBER.2015.7288171
Abstract: Dynamic reactive power reserve of power system is vital to improve transient voltage security. A novel definition of reactive power reserve considering transient voltage security in transient procession is proposed. Participation factor to evaluate reactive power reserve’s contribution to transient voltage stability is computed through trajectory sensitivity method. Then an optimization model to enhance transient voltage stability is built and a solving algorithm is proposed. Based on an analysis of the transient voltage stability characteristics of East China Power Grid, the effectiveness of the proposed dynamical reactive power reserve optimization approach for improving transient voltage stability of large-scale AC-DC hybrid power systems is verified.
Keywords: AC-DC power convertors; optimisation; power grids; power system control; power system transient stability; reactive power control; voltage regulators; East China power grid; dynamic reactive power reserve optimization method; large-scale AC-DC hybrid power systems; participation factor; trajectory sensitivity method; transient procession; transient voltage security improvement; transient voltage stability enhancement; Optimization; Power system dynamics; Power system stability; Reactive power; Stability analysis; Transient analysis; AC-DC hybrid power system; Dynamic reactive power reserve; optimization method; transient voltage stability (ID#: 16-10205)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7288171&isnumber=7287893
N. Ye, R. Geng, X. Song, Q. Wang and Z. Ning, “Hierarchic Topology Management by Decision Model and Smart Agents in Space Information Networks,” 2015 IEEE 17th International Conference on High Performance Computing and Communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conference on Embedded Software and Systems (ICESS), New York, NY, 2015, pp. 1817-1825. doi: 10.1109/HPCC-CSS-ICESS.2015.122
Abstract: Space information network, which is envisioned as a new type of self-organizing networks constituted by information systems of land, sea, air, and space, has attracted tremendous interest recently. In this paper, to improve the data delivery performance and the network scalability of space information networks, a new hierarchic topology management scheme based on decision model and smart agents is proposed. Different from the schemes studied in mobile ad hoc networks and wireless sensor networks, the proposed algorithm in space information networks introduces a decision model based on analytic hierarchy process (AHP) to first select cluster heads, and then forms non-overlapping k-hop clusters. The proposed dynamical self-maintenance mechanisms take not only the node mobility but also the cluster equalization into consideration. Smart mobile agents are used to migrate and duplicate functions of cluster heads in a recruiting way, besides of cluster merger/partition disposal, reaffiliation management and adaptive adjustment of information update period. Simulation experiments are performed to evaluate the performance of the proposed algorithm in terms of network scalability, overhead of clustering and reaffiliation frequency. It is shown from the analytical and simulation results that the proposed hierarchic topology management algorithm significantly improves the performance and the scalability of space information networks.
Keywords: analytic hierarchy process; computer network performance evaluation; information networks; merging; pattern clustering; telecommunication network topology; AHP; adaptive adjustment; cluster equalization; cluster head function duplication; cluster head function migration; cluster head selection; cluster merger disposal; cluster partition disposal; clustering overhead; data delivery performance; decision model; dynamical self-maintenance mechanisms; hierarchic topology management; information systems; information update period; network scalability improvement; node mobility; nonoverlapping k-hop clusters; performance evaluation; reaffiliation frequency; reaffiliation management; self-organizing networks; smart mobile agents; space information networks; Clustering algorithms; Network topology; Satellites; Scalability; Space vehicles; Topology; Wireless sensor networks; smart agent; topology management (ID#: 16-10206)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7336436&isnumber=7336120
S. Gulhane and S. Bodkhe, “DDAS Using Kerberos with Adaptive Huffman Coding to Enhance Data Retrieval Speed and Security,” Pervasive Computing (ICPC), 2015 International Conference on, Pune, 2015, pp. 1-6. doi: 10.1109/PERVASIVE.2015.7086987
Abstract: The increasing fad of deploying application over the web and store as well as retrieve database to/from particular server. As data stored in distributed manner so scalability, flexibility, reliability and security are important aspects need to be considered while established data management system. There are several systems for database management. After reviewing Distributed data aggregation service (DDAS) system which is relying on Blobseer it found that it provide a high level performance in aspects such as data storage as a Blob (Binary large objects) and data aggregation. For complicated analysis and instinctive mining of scientific data, Blobseer serve as a repository backend. WS-Aggregation is the another framework which is viewed as a web services but it is actually carried out aggregation of data. In this framework for executing multi-site queries a single-site interface is provided to the clients. Simple storage service (S3) is another type of storage utility. This S3 system provides an anytime available and low cost service. Kerberos is a method which provides a secure authentication as only authorized clients are able to access distributed database. Kerberos consist of four steps i.e. Authentication Key exchange, Ticket granting service Key exchange, Client/Server service exchange and Build secure communication. Adaptive Huffman method to writing (also referred to as Dynamic Huffman method) is associate accommodative committal to writing technique basic of Huffman coding. It permits compression as well as decompression of data and also permits building the code because the symbols square measure is being transmitted, having no initial information of supply distribution, that enables one-pass cryptography and adaptation to dynamical conditions in data.
Keywords: Huffman codes; Web services; cryptography; data mining; distributed databases; query processing; Blob; Blobseer; DDAS; Kerberos; WS-Aggregation; adaptive Huffman coding; authentication key exchange; binary large objects; client-server service exchange; data aggregation; data management system; data retrieval security; data retrieval speed; data storage; distributed data aggregation service system; distributed database; dynamic Huffman method; instinctive scientific data mining; multisite queries; one-pass cryptography; secure communication; Authentication; Catalogs; Distributed databases; Memory; Servers; XML; adaptive huffman method; blobseer; kerberos; simple storage service; ws aggregation (ID#: 16-10207)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7086987&isnumber=7086957
M. De Paula and G. G. Acosta, “Trajectory Tracking Algorithm for Autonomous Vehicles Using Adaptive Reinforcement Learning,” OCEANS 2015 - MTS/IEEE Washington, Washington, DC, 2015, pp. 1-8. doi: (not provided)
Abstract: The off-shore industry requires periodic monitoring of underwater infrastructure for preventive maintenance and security reasons. The tasks in hostile environments can be achieved automatically through autonomous robots like UUV, AUV and ASV. When the robot controllers are based on prespecified conditions they could not function properly in these hostile changing environments. It is beneficial to count with adaptive control strategies that are capable to readapt the control policies when deviations, from the desired behavior, are detected. In this paper, we present an online selective reinforcement learning approach for learning reference tracking control policies given no prior knowledge of the dynamical system. The proposed approach enables real-time adaptation of the control policies, executed by the adaptive controller, based on ongoing interactions with the non-stationary environments. Applications on surface vehicles under nonstationary and perturbed environments are simulated. The presented simulation results demonstrate the performance of this novel algorithm to find optimal control policies that solve the trajectory tracking control task in unmanned vehicles.
Keywords: adaptive control; intelligent robots; learning (artificial intelligence); mobile robots; optimal control; preventive maintenance; remotely operated vehicles; trajectory control; adaptive reinforcement learning; autonomous robots; autonomous vehicles; hostile environments; learning reference tracking control policies; nonstationary environments; off-shore industry; online selective reinforcement learning approach; optimal control policies; periodic monitoring; perturbed environments; robot controllers; security reasons; surface vehicles; trajectory tracking control task; underwater infrastructure; unmanned vehicles; Gaussian distribution; Monitoring; Robots; Security; Vehicles; Autonomous vehicles; cognitive control; reinforcement learning; trajectory tracking
(ID#: 16-10208)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7401861&isnumber=7401802
Bo Yang, Bo Li, Mao Yang, Zhongjiang Yan and Xiaoya Zuo, “Mi-MMAC: MIMO-Based Multi-Channel MAC Protocol for WLAN,” Heterogeneous Networking for Quality, Reliability, Security and Robustness (QSHINE), 2015 11th International Conference on, Taipei, 2015, pp. 223-226. doi: (not provided)
Abstract: In order to meet the proliferating demands in wireless local area networks (WLANs), the multi-channel media access control (MMAC) technology has attracted a considerable attention to exploit the increasingly scarce spectrum resources more efficiently. This paper proposes a novel multi-channel MAC to resolve the congestion on the control channel, named as Mi-MMAC, by multiplexing the control-radio and the data-radio as a multiple-input multiple-output (MIMO) array, working on both the control channel and the data channels alternately. Furthermore, we model Mi-MMAC as an M/M/k queueing system and obtain a closed-form approximate formula of the saturation throughput. Simulation results validate our model and analysis, and we demonstrate that the saturation throughput gain of the proposed protocol is close to 3.3 times compared with the dynamical channel assignment (DCA) protocol [1] under the few collisions condition.
Keywords: MIMO communication; access protocols; approximation theory; queueing theory; telecommunication congestion control; wireless LAN; wireless channels; DCA protocol; M/M/k queueing system; MIMO; Mi-MMAC; WLAN; closed form approximate formula; control channel; control radio; data channels; data radio; dynamical channel assignment; media access control; multichannel MAC protocol; multiple-input multiple-output array; scarce spectrum resources; DH-HEMTs; Mobile communication; Multiplexing; Protocols; Queueing analysis; Switches; Transceivers; Media access control; Multi-channel; Multiple-input multiple-output; Wireless LAN
(ID#: 16-10209)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7332572&isnumber=7332527
Y. Nakahira and Y. Mo, “Dynamic State Estimation in the Presence of Compromised Sensory Data,” 2015 54th IEEE Conference on Decision and Control (CDC), Osaka, 2015, pp. 5808-5813. doi: 10.1109/CDC.2015.7403132
Abstract: In this article, we consider the state estimation problem of a linear time invariant system in adversarial environment. We assume that the process noise and measurement noise of the system are l∞ functions. The adversary compromises at most γ sensors, the set of which is unknown to the estimation algorithm, and can change their measurements arbitrarily. We first prove that if after removing a set of 2γ sensors, the system is undetectable, then there exists a destabilizing noise process and attacker’s input to render the estimation error unbounded. For the case that the system remains detectable after removing an arbitrary set of 2γ sensors, we construct a resilient estimator and provide an upper bound on the l∞ norm of the estimation error. Finally, a numerical example is provided to illustrate the effectiveness of the proposed estimator design.
Keywords: invariance; linear systems; measurement errors; measurement uncertainty; state estimation; compromised sensory data; dynamic state estimation; estimation error; estimator design; l∞ functions; linear time invariant system; measurement noise; measurements arbitrarily; process noise; Estimation error; Robustness; Security; Sensor systems; State estimation (ID#: 16-10210)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7403132&isnumber=7402066
K. G. Vamvoudakis et al., “Autonomy and Machine Intelligence in Complex Systems: A Tutorial,” 2015 American Control Conference (ACC), Chicago, IL, 2015, pp. 5062-5079. doi: 10.1109/ACC.2015.7172127
Abstract: This tutorial paper will discuss the development of novel state-of-the-art control approaches and theory for complex systems based on machine intelligence in order to enable full autonomy. Given the presence of modeling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals and malicious attacks compromising the security of teams of complex systems, there is a need for approaches that respond to situations not programmed or anticipated in design. Unfortunately, existing schemes for complex systems do not take into account recent advances of machine intelligence. We shall discuss on how to be inspired by the human brain and combine interdisciplinary ideas from different fields, i.e. computational intelligence, game theory, control theory, and information theory to develop new self-configuring algorithms for decision and control given the unavailability of model, the presence of enemy components and the possibility of network attacks. Due to the adaptive nature of the algorithms, the complex systems will be capable of breaking or splitting into parts that are themselves autonomous and resilient. The algorithms discussed will be characterized by strong abilities of learning and adaptivity. As a result, the complex systems will be fully autonomous, and tolerant to communication failures.
Keywords: artificial intelligence; game theory; information theory; large-scale systems; learning systems; adaptive systems; complex systems; computational intelligence; control theory; learning; machine intelligence; network attacks; self-configuring algorithms; Complex systems; Computational modeling; Control systems; Machine intelligence; Mathematical model; Uncertainty; Vehicles; Autonomy; cyber-physical systems; networks (ID#: 16-10211)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7172127&isnumber=7170700
K. G. Vamvoudakis and J. P. Hespanha, “Model-Free Plug-n-Play Optimization Techniques to Design Autonomous and Resilient Complex Systems,” 2015 American Control Conference (ACC), Chicago, IL, 2015, pp. 5081-5081. doi: 10.1109/ACC.2015.7172129
Abstract: Summary form only given: This talk will focus on model-free distributed optimization based algorithms for complex systems with formal optimality and robustness guarantees. Given the presence of modeling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals and malicious attacks compromising the security of networked teams, there is a need for completely model-free plug-n-play approaches that respond to situations not programmed or anticipated in design, in order to guarantee mission completion. Unfortunately, existing schemes for complex systems do not take into account recent advances of computational intelligence. This talk will combine interdisciplinary ideas from different fields, i.e. computational intelligence, game theory, control theory, and information theory to develop new self-configuring algorithms for decision and control given the unavailability of model, the presence of enemy components and the possibility of measurement and jamming network attacks. Due to the adaptive nature of the algorithms, the complex systems will be capable of breaking or splitting into parts that are themselves autonomous and resilient. The proposed algorithms will be provided with guaranteed optimality and robustness and will be able to enable complete on-board autonomy, to multiply engagement capability, and enable coordination of distributed, heterogeneous teams of manned/unmanned vehicles and humans.
Keywords: large-scale systems; mobile robots; optimisation; vehicles; complex systems; computational intelligence; control theory; cooperative goals; enemy components; engagement capability; formal optimality; game theory; heterogeneous teams; information theory; interdisciplinary ideas; jamming network attacks; manned vehicles; measurement attacks; model-free plug-n-play optimization techniques; noncooperative goals; on-board autonomy; robustness guarantees; self-configuring algorithms; unmanned vehicles; Algorithm design and analysis; Complex systems; Computational intelligence; Computational modeling; Control systems; Optimization; Robustness (ID#: 16-10212)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7172129&isnumber=7170700
L. Pan, H. Voos, Y. Li, M. Darouach and S. Hu, “Uncertainty Quantification of Exponential Synchronization for a Novel Class of Complex Dynamical Networks with Hybrid TVD Using PIPC,” The 27th Chinese Control and Decision Conference (2015 CCDC), Qingdao, 2015, pp. 125-130. doi: 10.1109/CCDC.2015.7161678
Abstract: This paper investigates the Uncertainty Quantification (UQ) of Exponential Synchronization (ES) problems for a new class of Complex Dynamical Networks (CDNs) with hybrid Time-Varying Delay (TVD) and Non-Time-Varying Delay (NTVD) nodes by using coupling Periodically Intermittent Pinning Control (PIPC) which has three switched intervals in every period. Based on Kronecker product rules, Lyapunov Stability Theory (LST), Cumulative Distribution Function (CDF), and PIPC method, the robustness of the control algorithm with respect to the value of the final time is studied. Moreover, we assume a normal distribution for the time and used the Stochastic Collocation (SC) method [1] with different values of nodes and collocation points to quantify the sensitivity. For different numbers of nodes, the results show that the ES errors converge to zero with a high probability. Finally, to verify the effectiveness of our theoretical results, Nearest-Neighbor Network (NNN) and Barabási-Albert Network (BAN) consisting of coupled non-delayed and delay Chen oscillators are studied and to demonstrate that the accuracies of the ES and PIPC are robust to variations of time.
Keywords: Lyapunov methods; complex networks; convergence; delays; large-scale systems; normal distribution; periodic control; robust control; stochastic processes; switching systems (control); synchronisation; BAN; Barabási-Albert Network; CDF; CDN; Kronecker product rule; LST; Lyapunov stability theory; NNN; NTVD node; PIPC method; collocation points; complex dynamical network; control algorithm robustness; cumulative distribution function; delay Chen oscillator; error convergence; exponential synchronization problem; hybrid TVD; hybrid time-varying delay; nearest-neighbor network; nondelayed Chen oscillator; nontime-varying delay; normal distribution; periodically intermittent pinning control; probability; sensitivity quantification; stochastic collocation method; switched interval; time variation; uncertainty quantification; Artificial neural networks; Chaos; Couplings; Delays; Switches; Synchronization; Complex Dynamical Networks (CDNs); Exponential Synchronization (ES); Periodically Intermittent Pinning Control (PIPC);Time-varying Delay (TVD) (ID#: 16-10213)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7161678&isnumber=7161655
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