One of the most widespread techniques to evaluate various aspects of an existing manufacturing system is discrete-event simulation (DES). However, building a simulation model of a manufacturing system needs great reso...
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One of the most widespread techniques to evaluate various aspects of an existing manufacturing system is discrete-event simulation (DES). However, building a simulation model of a manufacturing system needs great resource expenditures. Automated data col-lection and model buildup can drastically reduce the time of the design phase as well as support model reusability. Since most of the manufacturing systems are controlled by low level controllers they store structure and control logic of the system to be modeled by a DES system. The paper introduces an ongoing research of PLC code processing method for automatic simulation model gen-eration of a conveyor system of a leading automotive factory.
Preserving connectivity of a network topology is a crucial aspect for multi-robot systems in order to perform almost any collaborative task. This problem turns out to be significantly challenging in the case of a hete...
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ISBN:
(纸本)9781457710957
Preserving connectivity of a network topology is a crucial aspect for multi-robot systems in order to perform almost any collaborative task. This problem turns out to be significantly challenging in the case of a heterogeneous multirobot system equipped with different sensors with limited field of view. Such an interaction scheme, in fact, is described by directed graphs (digraphs), for which, a few approaches have still been presented in literature. This paper addresses the problem of estimating an approximated minimum strongly connected digraph contained in a given digraph. A novel decentralized approach is proposed and its suitability is confirmed by simulations.
Mathematical models are constructed and used as a methodology of various functioning systems structure investigation and performance analysis. The main goal of mathematical model usage is to perform wholesome diagnost...
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Error propagation analysis is an important part of a system development process. This paper addresses a model based analysis of spreading of data errors through mechatronic systems. Error propagation models for such k...
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The present paper deals with control of system consists surge tank, pump a and pipeline. Model of this system is based on hydro-electrical analogy. For purpose of control it is designed a regulator with estimator. Reg...
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To electric furnace's characters as non-linear and time-varying, we designed a fuzzy PID controller, and made some simulation through MATLAB, at the same time we used a traditional PID controller and simulated, th...
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As described by digital system the language Verilog HDL is widely used in the circuit design, its own advantages to be able to use software language describe hardware features that makes it has good readability, porta...
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This paper deals with a three-phase inverter controller design for monobloc configuration of small swirl turbine. The aim is an phasing of the system to grid. A simulation design is described which leads to cascade co...
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Wind speed forecasting is required for ensuring an efficient utilization of the wind power generated by wind turbines. This paper purposes the short-term wind speed forecasting in a 2-dimesional input space using the ...
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ISBN:
(纸本)9781467323284
Wind speed forecasting is required for ensuring an efficient utilization of the wind power generated by wind turbines. This paper purposes the short-term wind speed forecasting in a 2-dimesional input space using the developed k-nearest neighbor (k-NN) classifier. As well, the effects of the nearest neighbor number and the selected distance metric on the wind speed forecasting were analyzed and many useful inferences were mined in order to minimize the forecasting error. The results have shown that the k-NN classifier which uses wind direction and relative humidity parameters achieved the best forecasting results for k=10 in the Minkowski distance metric. On the other hand, the k-NN classifier which uses wind direction and atmosphere pressure parameters gave the worst forecasting results for k=1 in the Euclidean distance metric.
Solar radiation prediction has a great importance in electricity generation from solar energy and helps to size photovoltaic power systems. Therefore, the solar radiation parameter was predicted at 10-min intervals in...
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ISBN:
(纸本)9781467323284
Solar radiation prediction has a great importance in electricity generation from solar energy and helps to size photovoltaic power systems. Therefore, the solar radiation parameter was predicted at 10-min intervals in this study. Outside temperature, outside humidity and barometric pressure parameters were used as meteorological input variables by the developed k-nearest neighbor (k-NN) classifier. On the one hand, it is mined that solar radiation prediction was affected by the number of nearest neighbors, the dimension of input parameters and the type of distance metrics. On the other hand, it is shown that the k-NN classifier which uses Euclidean distance metric for k=4 in 3-dimensional input space outperformed the other models in terms of the prediction accuracy. Adversely, the k-NN classifier which only uses barometric pressure input provided the weakest prediction performance for k=15 in Euclidean distance metric.
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