For those refineries which have to deal with different types of crude oil, blending is an attractive solution to obtain a quality feedstock. In this paper, a novel scheduling strategy is proposed for a practical crude...
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For those refineries which have to deal with different types of crude oil, blending is an attractive solution to obtain a quality feedstock. In this paper, a novel scheduling strategy is proposed for a practical crude oil blending process. The objective is to keep the property of feedstock, mainly described by the true boiling point (TBP) data, consistent and suitable. Firstly, the mathematical model is established. Then, a heuristically initialized hybrid iterative (HIHI) algorithm based on a two-level optimization structure, in which tabu search (TS) and differential evolution (DE) are used for upper-level and lower-level optimization, respectively, is proposed to get the model solution. Finally, the effectiveness and efficiency of the scheduling strategy is validated via real data from a certain refinery.
Electrical impedance tomography (EIT) is a technique for reconstructing conductivity of an inhomogeneous medium by injecting currents at the boundary of an object and measuring the resulting changes in voltage. The SN...
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An adaptive sliding mode speed and position observer for sensorless control of brushless DC motor (BLDCM) is proposed in this paper. According the mathematical model of BLDCM, the sliding surface was defined based on ...
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ISBN:
(纸本)9787894631046
An adaptive sliding mode speed and position observer for sensorless control of brushless DC motor (BLDCM) is proposed in this paper. According the mathematical model of BLDCM, the sliding surface was defined based on the errors between actual and estimated currents. Equivalent control and model reference adaptive control (MRAC) is used to obtain position and speed signals of the rotor. The Lyapunov theory is introduced to prove the convergence of this system. A sensorless control system for BLDCM based on the sliding mode observer is implemented. The stability of this observer which shows good robustness is not influenced by both load disturbance and measurement noise. The result of simulation shows that the proposed method can correctly estimate the speed and position of the rotor, and the system has good dynamic and static perf ormances.
A model structure for stationary emission models is presented. The emissions NO x , soot and opacity are separately modeled. Model inputs are the air mass flow rate, charge air pressure, intake temperature, the locati...
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A model structure for stationary emission models is presented. The emissions NO x , soot and opacity are separately modeled. Model inputs are the air mass flow rate, charge air pressure, intake temperature, the location of mass fraction burned 50% and the engine operation point. Local polynomials are trained for each operation point, defined by engine speed and injection quantity. To increase accuracy a selection algorithm of the significant regressors is presented. The local models are composed by means of weighting functions, depending on the engine operation points, to global emission models. For a rasterized operation range, the weighting can be interpreted as a linear interpolation of local models. This enables an easy implementation to common electronic control units (ECUs). Measurements from a CR-Diesel engine show the quality of the models.
Hailstone is one of main meteorological disasters and it is difficult to forecast effectively. In this paper, a new hail echo detection method based on time series association rules was proposed and a hail echo automa...
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In this paper, a new on-line soft sensing method is proposed for component concentrations of sodium aluminate solution. With this sensing strategy, real-time control and optimization can be realized in aluminate produ...
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ISBN:
(纸本)9781424463343
In this paper, a new on-line soft sensing method is proposed for component concentrations of sodium aluminate solution. With this sensing strategy, real-time control and optimization can be realized in aluminate production plants. Several advance techniques are used, such as PLS (Partial Least Squares), Hammerstein model, recurrent neural networks and least square algorithm. Industrial experiment results show that the proposed soft sensing algorithm is effective.
Wireless sensor networks (WSNs) have many applications in home and industrial automation, and the management and integration of WSNs into Internet and IP-based networks is still getting tremendous interesting. This pa...
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Wireless sensor networks (WSNs) have many applications in home and industrial automation, and the management and integration of WSNs into Internet and IP-based networks is still getting tremendous interesting. This paper presents a micro SOA-model as part of a 4-layered, SOA-based architecture targeting resource-constrained devices with 48 KB of ROM and 10 KB of RAM. The key idea in this model is trying to implement SOA concepts using WSN protocols instead of trying to port the SOA protocols from IT-business world. Our micro model is based on the mIP protocol and it uses the HTTP philosophy instead of the HTTP protocol itself. The middleware layer in our architecture manages the simultaneous access to the WSN and filters the verbose information in a HTTP request to the WSN. It also manages the events and the service description of all devices in the network as well as it provides many other tasks like DNS, firewall, security, and authorization. Furthermore the paper presents a new idea for compressing XML and JSON messages based on a new concept of exchanging a common vocabulary between the networked embedded devices. Our results show that using JSON format instead of XML, or applying our zipping algorithm on them has many advantages in terms of network overhead and power consumption.
This paper presents the control design via the combination of the neural predictive controller and the neurofuzzy controller. The neuro-fuzzy controller type of ANFIS works in parallel with the neural predictive contr...
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ISBN:
(纸本)9789604741991
This paper presents the control design via the combination of the neural predictive controller and the neurofuzzy controller. The neuro-fuzzy controller type of ANFIS works in parallel with the neural predictive controller and adjust the output of the predictive controller, in order to enhance predicted inputs. The performance of our proposal is demonstrated on the Continuous Stirred-Tank Reactor control problem with disturbances.
A control method for small domestic power plants using renewable energy is described in this paper. This method is not only capable of optimizing the working point of the plant but also implements active power factor ...
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In view of the problems existing in the prediction methods of coal and gas outburst, a method for prediction of coal and gas outburst based on multi-agent information fusion is proposed. In the method, considering the...
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