1,684 research outputs found
Leader-following Consensus of Multi-agent Systems over Finite Fields
The leader-following consensus problem of multi-agent systems over finite
fields is considered in this paper. Dynamics of each agent is
governed by a linear equation over , where a distributed control
protocol is utilized by the followers.Sufficient and/or necessary conditions on
system matrices and graph weights in are provided for the
followers to track the leader
Control of Discrete Event Systems
Discrete Event Systems (DES) are a special type of dynamic systems. The state of these systems changes only at discrete instants of time and the term event is used to represent the occurrence of discontinuous changes (at possibly unknown intervals). Different Discrete Event Systems models are currently used for specification, verification, synthesis as well as for analysis and evaluation of different qualitative and quantitative properties of existing physical systems.
The main focus of this paper is the presentation of the automata and formal language model for DES introduced by Raniadge and Wonham in 1985. This model is suitable for the examination of some important control theoretic issues, such as controllability and observability from the qualitative point of view, and provides a good basis for modular synthesis of controllers. We will also discuss an Extended State Machine and Real-Time Temporal Logic model introduced by Ostroff and Wonham in [OW87]. It incorporates an explicit notion of time and means for specification and verification of discrete event systems using a temporal logic approach. An attempt is made to compare this model of DES with other ones
Observability and Decentralized Control of Fuzzy Discrete Event Systems
Fuzzy discrete event systems as a generalization of (crisp) discrete event
systems have been introduced in order that it is possible to effectively
represent uncertainty, imprecision, and vagueness arising from the dynamic of
systems. A fuzzy discrete event system has been modelled by a fuzzy automaton;
its behavior is described in terms of the fuzzy language generated by the
automaton. In this paper, we are concerned with the supervisory control problem
for fuzzy discrete event systems with partial observation. Observability,
normality, and co-observability of crisp languages are extended to fuzzy
languages. It is shown that the observability, together with controllability,
of the desired fuzzy language is a necessary and sufficient condition for the
existence of a partially observable fuzzy supervisor. When a decentralized
solution is desired, it is proved that there exist local fuzzy supervisors if
and only if the fuzzy language to be synthesized is controllable and
co-observable. Moreover, the infimal controllable and observable fuzzy
superlanguage, and the supremal controllable and normal fuzzy sublanguage are
also discussed. Simple examples are provided to illustrate the theoretical
development.Comment: 14 pages, 1 figure. to be published in the IEEE Transactions on Fuzzy
System
Testable Design for Positive Control Flipping Faults in Reversible Circuits
Fast computational power is a major concern in every computing system. The advancement of the fabrication process in the present semiconductor technologies provides to accommodate millions of gates per chip and is also capable of reducing the size of the chips. Concurrently, the complex circuit design always leads to high power dissipation and increases the fault rates. Due to these difficulties, researchers explore the reversible logic circuit as an alternative way to implement the low-power circuit design. It is also widely applied in recent technology trends like quantum computing. Analyzing the correct functional behavior of these circuits is an essential requirement in the testing of the circuit. This paper presents a testable design for the k-CNOT based circuit capable of diagnosing the Positive Control Flipping Faults (PCFFs) in reversible circuits. The proposed work shows that generating a single test vector that applies to the constructed design circuit is sufficient for covering the PCFFs in the reversible circuit. Further, the parity-bit operations are augmented to the constructed testable circuit that produces the parity-test pattern to extract the faulty gate location of PCFFs. Various reversible benchmark circuits are used for evaluating the experimental results to establish the correctness of the proposed fault diagnosis technique. Also a comparative analysis is performed with the existing work
HybMT: Hybrid Meta-Predictor based ML Algorithm for Fast Test Vector Generation
Testing an integrated circuit (IC) is a highly compute-intensive process. For
today's complex designs, tests for many hard-to-detect faults are typically
generated using deterministic test generation (DTG) algorithms. Machine
Learning (ML) is being increasingly used to increase the test coverage and
decrease the overall testing time. Such proposals primarily reduce the wasted
work in the classic Path Oriented Decision Making (PODEM) algorithm without
compromising on the test quality. With variants of PODEM, many times there is a
need to backtrack because further progress cannot be made. There is thus a need
to predict the best strategy at different points in the execution of the
algorithm. The novel contribution of this paper is a 2-level predictor: the top
level is a meta predictor that chooses one of several predictors at the lower
level. We choose the best predictor given a circuit and a target net. The
accuracy of the top-level meta predictor was found to be 99\%. This leads to a
significantly reduced number of backtracking decisions compared to
state-of-the-art ML-based and conventional solutions. As compared to a popular,
state-of-the-art commercial ATPG tool, our 2-level predictor (HybMT) shows an
overall reduction of 32.6\% in the CPU time without compromising on the fault
coverage for the EPFL benchmark circuits. HybMT also shows a speedup of 24.4\%
and 95.5\% over the existing state-of-the-art (the baseline) while obtaining
equal or better fault coverage for the ISCAS'85 and EPFL benchmark circuits,
respectively.Comment: 9 pages, 7 figures and 7 tables. Changes from the previous version:
We performed more experiments with different regressor models and also
proposed a new neural network model, HybNN. We report the results for the
EPFL benchmark circuits (most recent and large) and compare our results
against a popular commercial ATPG too
Passivity-preserving parameterized model order reduction using singular values and matrix interpolation
We present a parameterized model order reduction method based on singular values and matrix interpolation. First, a fast technique using grammians is utilized to estimate the reduced order, and then common projection matrices are used to build parameterized reduced order models (ROMs). The design space is divided into cells, and a Krylov subspace is computed for each cell vertex model. The truncation of the singular values of the merged Krylov subspaces from the models located at the vertices of each cell yields a common projection matrix per design space cell. Finally, the reduced system matrices are interpolated using positive interpolation schemes to obtain a guaranteed passive parameterized ROM. Pertinent numerical results validate the proposed technique
Design-Time Quantification of Integrity in Cyber-Physical-Systems
In a software system it is possible to quantify the amount of information
that is leaked or corrupted by analysing the flows of information present in
the source code. In a cyber-physical system, information flows are not only
present at the digital level, but also at a physical level, and to and fro the
two levels. In this work, we provide a methodology to formally analyse a
Cyber-Physical System composite model (combining physics and control) using an
information flow-theoretic approach. We use this approach to quantify the level
of vulnerability of a system with respect to attackers with different
capabilities. We illustrate our approach by means of a water distribution case
study
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