Human trust plays a crucial role in Human-Machine Interactions (HMIs) within autonomous systems. This paper delves into the factors that influence human trust in machines, including varying error rates and types made ...
Human trust plays a crucial role in Human-Machine Interactions (HMIs) within autonomous systems. This paper delves into the factors that influence human trust in machines, including varying error rates and types made by the machine, as well as the human's ability to intervene and rectify errors. To explore these factors, we conducted three scenarios involving a simulated claw robot navigating through multiple objects to detect and locate a target object. The first scenario examined the effect of changing error rates on human trust in the machine. In the second scenario, we investigated how variability in speed and accuracy of reaching the target impacted human trust. Lastly, we explored whether human trust in the machine changed when individuals had the capability to intervene and correct severe errors made by the machine. We then proposed a regression model to estimate human trust. Our results showed that human trust is significantly affected by changes in error rates. Our participants reported a higher trust on robot with low speed but higher accuracy in performing the task than the robot with high speed but lower accuracy. Interestingly, the ability to intervene and correct the robot's errors improved the participants' trust in the robot. Our regression result showed that we can estimate trust using different type of errors committed by machine which can be applied in real world scenarios.
The energy meter is a widely used digital-analog electronic system. However, metering accuracy is inevitably influenced by factors such as ambient temperature, load current, and component tolerance. This paper introdu...
The energy meter is a widely used digital-analog electronic system. However, metering accuracy is inevitably influenced by factors such as ambient temperature, load current, and component tolerance. This paper introduces a method utilizing digital twin models to analyze the consistency of metering accuracy in a new single-phase smart meter prototype. An electro-thermal coupling model incorporating a temperature compensation algorithm is established, and the metering accuracy is solved using a surrogate model. By employing the Monte Carlo method, a batch of product samples is generated to determine the impact of varying ambient temperature and load current conditions on the metering accuracy’s consistency within the maximum operating range. The results of this study provides a valuable foundation for robust design and reliability optimization of the energy meter.
We analyze a dual-port grid-forming (GFM) control for power systems containing ac and dc transmission, converter-interfaced generation and energy storage, and legacy generation. To operate such a system and provide st...
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In this paper, we consider the unconstrained distributed optimization problem, in which the exchange of information in the network is captured by a directed graph topology, thus, nodes can only communicate with their ...
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In this paper, we consider the unconstrained distributed optimization problem, in which the exchange of information in the network is captured by a directed graph topology, thus, nodes can only communicate with their neighbors. Additionally, in our problem, the communication channels among the nodes have limited bandwidth. In order to alleviate this limitation, quantized messages should be exchanged among the nodes. For solving this distributed optimization problem, we combine a gradient descent method with a distributed quantized consensus algorithm (which requires the nodes to exchange quantized messages and converges in a finite number of steps). Specifically, at every optimization step, each node (i) performs a gradient descent step (i.e., subtracts the scaled gradient from its current estimate), and (ii) performs a finite-time calculation of the quantized average of every node's estimate in the network. As a consequence, this algorithm approximately mimics the centralized gradient descent algorithm. We show that our algorithm asymptotically converges to a neighborhood of the optimal solution with linear convergence rate. The performance of the proposed algorithm is demonstrated via simple illustrative examples.
This paper studied the design of a predictive current control strategy with fault tolerance and reactive power minimization applied to a multi-modular topology based on indirect 2-level matrix converters fed by a six-...
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As power electronics technology continues to advance, the prevalence of switching quantity interface circuits has grown in diverse domains, encompassing industrial production and everyday civilian applications. An ana...
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ISBN:
(数字)9798350329988
ISBN:
(纸本)9798350329995
As power electronics technology continues to advance, the prevalence of switching quantity interface circuits has grown in diverse domains, encompassing industrial production and everyday civilian applications. An analysis of operational data from these circuits, along with an assessment of their overall health, proves instrumental in the timely detection and resolution of operational anomalies. This holds paramount significance in upholding the reliability of these interface circuits. Nevertheless, tracking the degradation trajectory of the core components during their operational lifespan poses a challenge. Typically, only two states, normal and abnormal, are readily discernible, making direct health assessment elusive. To address this issue, this study introduces a health assessment methodology for the fundamental components of switch quantity interface circuits based on active excitation testing. Through the application of active excitation, the performance decay profile of the optical coupler is ascertained, solving the problem of capturing the degradation process within these circuits. This approach facilitates the stable and precise characterization of the health status of switching quantity interface circuits. The health assessment method presented in this paper is characterized by modest computational resource demands and a reduced reliance on expert knowledge. It is adept at quantitatively delineating the health status of switch-quantity interface circuits with precision, thereby offering guidance for the maintenance and replacement of pivotal electronic components within these circuits. In doing so, it contributes to the assurance of operational dependability and an extension of the service life of switch quantity interface circuits.
In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topology over digital channels that have lim...
In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topology over digital channels that have limited capacity (and hence information should be quantized). Distributed methods in which nodes use quantized communication yield a solution at the proximity of the optimal solution, hence reaching an error floor that depends on the quantization level used; the finer the quantization the lower the error floor. However, it is not possible to determine in advance the optimal quantization level that ensures specific performance guarantees (such as achieving an error floor below a predefined threshold). Choosing a very small quantization level that would guarantee the desired performance, requires information packets of very large size, which is not desirable (could increase the probability of packet losses, increase delays, etc) and often not feasible due to the limited capacity of the channels available. In order to obtain a communication-efficient distributed solution and a sufficiently close proximity to the optimal solution, we propose a quantized distributed optimization algorithm that converges in a finite number of steps and is able to adjust the quantization level accordingly. The proposed solution uses a finite-time distributed optimization protocol to find a solution to the problem for a given quantization level in a finite number of steps and keeps refining the quantization level until the difference in the solution between two successive solutions with different quantization levels is below a certain pre-specified threshold. Therefore, the proposed algorithm progressively refines the quantization level, thus eventually achieving low error floor with a reduced communication burden. The performance gains of the proposed algorithm are demonstrated via illustrative examples.
This paper presents two methods for implementing complex-valued sliding mode controllers in three-phase power converters. The paper includes the description of the algorithms and a detailed analysis of the proposed im...
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It is shown that pumping complexes of industrial and communal water supply are complex energy-intensive objects with low controllability in both normal and emergency modes of operation. It is proposed to use reversibl...
It is shown that pumping complexes of industrial and communal water supply are complex energy-intensive objects with low controllability in both normal and emergency modes of operation. It is proposed to use reversible modes of operation of turbomechanisms to increase the controllability of pump complex equipment. The structure of the system of active regulation of pump complex parameters with various options for including the adjustable hydroturbine unit has been developed. It is shown that active devices can perform both regulatory and protective functions. A device for controlling and protecting the pumping unit against water hammer based on an active water flow energy quencher is proposed. The algorithm of operation of the software control device of the electrohydraulic equipment protection system against excess pressure in the hydraulic network has been developed.
By means of the linear parameter-varying (LPV) Fundamental Lemma, we derive novel data-driven predictive control (DPC) methods for LPV systems. In particular, we present output-feedback and state-feedback-based LPV-DP...
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