We address the problem of state estimation for multi-output continuous-time linear systems, for which an attacker may have control over some of the sensors and inject (potentially unbounded) additive noise into some o...
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ISBN:
(纸本)9781479917730
We address the problem of state estimation for multi-output continuous-time linear systems, for which an attacker may have control over some of the sensors and inject (potentially unbounded) additive noise into some of the measured outputs. To characterize the resilience of a system against such sensor attacks, we introduce a new notion of observability -- termed "observability under attacks" -- that addresses the question of whether or not it is possible to uniquely reconstruct the state of the system by observing its inputs and outputs over a period of time, with the understanding that some of the available system's outputs may have been corrupted by the opponent. We provide computationally efficient tests for observability under attacks that amount to testing the (standard) observability for an appropriate finite set of systems. In addition, we propose two state estimation algorithms that permit the state reconstruction in spite of the attacks. One of these algorithms uses observability Gramians and a finite window of measurements to reconstruct the initial state. The second algorithm takes the form of a switched observer that asymptotically converges to the correct state estimate in the absence of additive noise and disturbances, or to a neighborhood of the correct state estimate in the presence of bounded noise and disturbances.
This paper presents optimal generation scheduling for minimization of fuel consumption (FC) in an offshore support vessel with a dynamic positioning system and diesel generator (DG) sets of 8000 kW total capacity. FC ...
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ISBN:
(纸本)9781479917631
This paper presents optimal generation scheduling for minimization of fuel consumption (FC) in an offshore support vessel with a dynamic positioning system and diesel generator (DG) sets of 8000 kW total capacity. FC is analyzed for equal load sharing among equal capacity DGs, optimal load sharing among equal capacity DGs, and optimal load sharing among unequal capacity DGs. Due to nonlinear specific FC (SFC) curves of the diesel engines, a Genetic Algorithm is used for optimal load sharing. The SFC-vs-load relationship obtained from Brake SFC (BSFC) map of the diesel engines is characterized using a cubic spline interpolation. A solution to the problem is attained by comparing yearly fuel consumption in the three cases for the load profile of target vessel. This method can be applied to any vessel equipped with multiple generating units. A vessel with proper selection of DG capacities and closed bus-tie can achieve maximum fuel savings; however, when deciding the DG capacity and load scheduling, it is necessary to consider fuel consumption alongside concerns such as optimizing exhaust emissions after-treatment, ensuring adequate power availability for essential services, and scheduling engine maintenance.
The correct determination of the shelf mass including content is very important for the proper function of a universal shelf stacker (USS) drives life and construction USS so that these elements were not overloaded. W...
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Surveillance systems require advanced algorithms able to make decisions without a human operator or with minimal assistance from human operators. In this paper we propose a novel approach for dynamic topic modeling to...
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Surveillance systems require advanced algorithms able to make decisions without a human operator or with minimal assistance from human operators. In this paper we propose a novel approach for dynamic topic modeling to detect abnormal behaviour in video sequences. The topic model describes activities and behaviours in the scene assuming behaviour temporal dynamics. The new inference scheme based on an Expectation-Maximisation algorithm is implemented without an approximation at intermediate stages. The proposed approach for behaviour analysis is compared with a Gibbs sampling inference scheme. The experiments both on synthetic and real data show that the model, based on Expectation-Maximisation approach, outperforms the one, based on Gibbs sampling scheme.
The present paper introduces a procedure to recover an inverse parametric linear or quadratic programming problem from a given polyhedral partition over which a continuous piecewise affine function is defined. The sol...
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Peer review (e.g., review of research papers) is essential for the success of the scientific community. In peer review, the reviewers voluntarily exert costly effort in reviewing papers. Hence, it is important to desi...
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ISBN:
(纸本)9781479980093
Peer review (e.g., review of research papers) is essential for the success of the scientific community. In peer review, the reviewers voluntarily exert costly effort in reviewing papers. Hence, it is important to design mechanisms to elicit high effort from reviewers. Exploiting the fact that the researchers interact with each other repeatedly (e.g., by submitting and reviewing papers over years), we propose a rating and matching mechanism to elicit high effort from reviewers. Our proposed mechanism overcomes two major difficulties, namely adverse selection (i.e., the unidentifiable quality of heterogeneous reviewers) and moral hazard (i.e., the unobservable effort levels from reviewers). Specifically, our proposed mechanism assigns and updates ratings for the researchers, and matches researchers' papers to reviewers with similar ratings. In this way, the mechanism identifies different types of reviewers by their ratings, and incentivizes different reviewers to exert high effort. Focusing on the matching rule, we first provide design guidelines for a general matching rule that leads the system to an equilibrium, where the reviewers' types are identified and their high efforts are elicited. Then we study in detail a baseline matching rule that assigns each researcher's paper to one of the two reviewers with the closest ratings, provide guidelines of how to choose the initial ratings, and analyze equilibrium review quality and equilibrium ratings. Finally, we extend the baseline matching rule to two classes. The first extension provides extra reward and/or punishment by adjusting the probabilities of matching each researcher's paper to its neighbors. The second extension provides extra reward and/or punishment by allowing to match each researcher's paper to reviewers other than its neighbors. We prove that it is beneficial (in the sense that the optimal equilibrium review quality is higher) to reward reviewers in the first extension, and to punish reviewers in the sec
In this paper the regulation problem for linear continuous-time systems by linear state-feedback under linear state and/or control constraints is investigated. This problem, named the Linear Constrained Regulation Pro...
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An experimental study was carried out on a piezoelectric actuator in order to explore the benefits of a mathematical formula [1], that describes the output of the inverse compensation when an inverse Prandtl-Ishlinski...
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ISBN:
(纸本)9781479917730
An experimental study was carried out on a piezoelectric actuator in order to explore the benefits of a mathematical formula [1], that describes the output of the inverse compensation when an inverse Prandtl-Ishlinskii hysteresis model is applied as a feedforward compensator. The inverse Prandtl-Ishlinskii was first formulated and applied for compensation of hysteresis nonlinearities of a piezoelectric actuator. The theoretical formula was afterwards employed to construct an H_∞ feedback control. The controller was calculated and applied to the piezoelectric actuator with the inverse feedforward model. The experimental results verify the effectiveness of the controller and the benefits that the theoretical formula of the inverse compensation can contribute.
To be utilized in the smart charging of plug-in electric vehicles, this paper proposes semiparametric conditional mean and variance models for the daily density forecasting of the electricity load. The mean is modeled...
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ISBN:
(纸本)9781479977970
To be utilized in the smart charging of plug-in electric vehicles, this paper proposes semiparametric conditional mean and variance models for the daily density forecasting of the electricity load. The mean is modeled by means of an autoregressive moving average model with exogenous inputs (ARMAX), whereas several options for the variance evolution are investigated, starting with modeling the variance as a power of the conditional mean, then as a piecewise constant function, and finally as a generalized autoregressive conditional heteroskedasticity (GARCH) model. Due to the possible non-Gaussianity of the distribution of the stochastic components, a quasi-maximum likelihood estimation (QMLE) with the Pearson type IV (P-IV) distribution is also considered, apart from the estimation with the Gaussianity assumption. Moreover, the daily density forecasts are generated in a nonparametric manner by propagating samples from the stochastic components iteratively through the available model. These strategies, involving different options for variance modeling and estimation, are compared in terms of their forecast performances on two representative phase currents from the low voltage cables of medium-to-low voltage transformers in the Netherlands. The results indicate that the QMLE with the Gaussianity assumption performs better due to the additional complexity of the P-IV distribution on estimation. Concerning the variance models, the piecewise constant and GARCH models are more preferable when processing phase currents exhibiting only daily seasonality, and the model as a power of the conditional mean outperforms the others if both daily and weekly seasonality and hence more complexity is present.
The sinking of the Titanic is typically blamed on human, design and construction errors. But what of the iceberg that did the damage? Was it a lone berg, or one of many in the area? And should it have been that far so...
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