It is a key issue in building operation management how to design an open and ubiquitous information system for diversity buildings of smart cities. This paper presents an operation management cloud ecosystem for smart...
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ISBN:
(纸本)9781538604915
It is a key issue in building operation management how to design an open and ubiquitous information system for diversity buildings of smart cities. This paper presents an operation management cloud ecosystem for smart buildings based on the technologies of Internet of Things (IoT) and cloud computing. It contains four levels: operation management application level, Internet of things platform, networking level, node level. The IoT platform provides hosting and computing, cloud storage, data storage for smart buildings. Networking level takes the responsibility for networking for intelligent hardware and smart terminals from the device level. With the building operation management applications, the cloud ecosystem is able to provide services of monitoring, controlling, management, and real-time optimization for smart buildings in cities.
This paper considers the convergence of iterative learning control(ILC) for discrete time systems with data quantization. Two iterative learning control schemes are proposed by using the system output quantized signal...
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ISBN:
(纸本)9781509009107
This paper considers the convergence of iterative learning control(ILC) for discrete time systems with data quantization. Two iterative learning control schemes are proposed by using the system output quantized signal and tracking error quantized signal. Based on the super-vector formulation of the ILC systems, the convergence conditions for the two iterative learning control schemes are given respectively. It is shown that the ILC law with system output quantized signal only make the tracking error converge to a bound, thus the ILC law with tracking error quantized signal can obtain zero tracking error. The results are illustrated by a numerical example.
In this work, we present an extension to a linear Model Predictive control (MPC) scheme that plans external contact forces for the robot when given multiple contact locations and their corresponding friction cone. To ...
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The sensitivity function is discussed for the linear time-invariant SISO minimum-phase system with unknown order and uncertain relative degree, which is under the active disturbance rejection control (ADRC). The desig...
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The sensitivity function is discussed for the linear time-invariant SISO minimum-phase system with unknown order and uncertain relative degree, which is under the active disturbance rejection control (ADRC). The design of the ADRC scheme is also discussed. It is proved that ADRC can guarantee the closed-loop stability when the relative degree of the system is bounded. The numerical examples demonstrate that the ADRC scheme can be applied to the different systems without retuning the parameters.
Distributed optical fiber sensors have been widely used to monitor temperature, strain, vibration, and so on. Specifically, the sensors based on Brillouin scattering have been studied extensively to measure the strain...
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Distributed optical fiber sensors have been widely used to monitor temperature, strain, vibration, and so on. Specifically, the sensors based on Brillouin scattering have been studied extensively to measure the strain or temperature along an oDtical fiber.
With the rapid development of distributed energy resources (DERs), it is of vital importance to develop a well-designed transmission cost allocation scheme to reflect the contributions of DERs to the power system. In ...
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We investigate solvable-unsolvable phase transitions in the single-machine scheduling (SMS) problem. SMS is at the core of practical problems such as telescope and satellite scheduling and manufacturing. To study the ...
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Accurately monitoring the system's operating point is central to the reliable and economic operation of an electric power grid. Power system state estimation (PSSE) aims to obtain complete voltage magnitude and an...
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The development of heat metering has promoted the development of statistic models for the prediction of heat demand, due to the large amount of availab.e data, or big data. Weather data have been commonly used as inpu...
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The development of heat metering has promoted the development of statistic models for the prediction of heat demand, due to the large amount of availab.e data, or big data. Weather data have been commonly used as input in such statistic models. In order to understand the impacts of direct solar radiance and wind speed on the model performance comprehensively, a model based on Elman neural networks (ENN) was adopted, of which the results can help heat producers to optimize their production and thus mitigate costs. Compared with the measured heat demand, the introduction of wind speed and direct solar radiation has opposite impacts on the performance of ENN and the inclusion of wind speed can improve the prediction accuracy of ENN. However, ENN cannot benefit from the introduction of both wind speed and direct solar radiation simultaneously.
A new turning-mechanism for Amoeba-like Robot was proposed in this paper, which based on the amoeba-like robot kinematics characteristics of tail contracting and skin flipping. First, one kind of variable-speed node c...
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