Distributed controlsystems (DCS) are based on assignments of control loops and supervision points to different units. In a first approach, these assignments are made statically and following given distribution criter...
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This paper describes a neural predictive control toolbox developed in Matlab/Simulink environment. The application permits all phases of the system design: simulation of the plant by means of any Simulink model, loadi...
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Distributed controlsystems (DCS) are based on assignments of control loops and supervision points to different units. In a first approach, these assignments are made statically and following given distribution criter...
详细信息
Distributed controlsystems (DCS) are based on assignments of control loops and supervision points to different units. In a first approach, these assignments are made statically and following given distribution criteria. This paper presents a proposal of communications system over a DCS which allows the interchanging of assignments between the control units. The objective is to provide a frame for dynamical load balancing in the system with reactivity against meaningful variables in the system such as changes in the process, traffic demands or computing load in every processor.
Modelling and simulation are inseparable procedures that include the complex activities associated with the construction of models representing real processes, and experimentation with the models to obtain data on the...
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This paper describes a neural predictive control toolbox developed in Matlab/Simulink environment. The application permits all phases of the system design: simulation of the plant by means of any Simulink model, loadi...
详细信息
This paper describes a neural predictive control toolbox developed in Matlab/Simulink environment. The application permits all phases of the system design: simulation of the plant by means of any Simulink model, loading of input/output data, definition of the neural network architecture, training, and, finally, application of the predictive control strategy based on the neural network model.
Modelling and simulation are inseparable procedures that include the complex activities associated with the construction of models representing real processes, and experimentation with the models to obtain data on the...
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Modelling and simulation are inseparable procedures that include the complex activities associated with the construction of models representing real processes, and experimentation with the models to obtain data on the behaviour of the system being modelled. This paper shows how an objected-oriented modelling language can be used to build the dynamic simulation model of an industrial production process that contains both continuous and bath units. The selected case of study is an essential part of a sugar factory: the sugarhouse.
作者:
Rogelio MazaedaCéar de PradaISPJAE
Cuba at present with the Dpt. Systems Engineering and Automatic Control Faculty of Sciences University of Valladolid c/ Real de Burgos s/n 47011 Valladolid Spain. tlf. +34 983 423162 Fax +34 983 423161 Dpt. Systems Engineering and Automatic Control
Faculty of Sciences University of Valladolid c/ Real de Burgos s/n 47011 Valladolid Spain. tlf. +34 983 423164 Fax +34 983 423161.
Iterative Feedback Tuning (IFT) is a tuning method that adjust on-line the parameters in the controller so that a performance criterion is minimised. The IFT method uses only experimental data obtained from the closed...
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Iterative Feedback Tuning (IFT) is a tuning method that adjust on-line the parameters in the controller so that a performance criterion is minimised. The IFT method uses only experimental data obtained from the closed loop system without assuming knowledge of the plant or perturbations models. In this paper the application of IFT to the tuning of a PID controller of a pilot plant is reported. The impact on the achieved system performance due to time weighting of the control error is particularly addressed.
Synchronization problems are a well-known key topic in Distributed controlsystems. Most of the functionalities are implicitly based on the time consistency along the system. At the same time, general purpose operatin...
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Synchronization problems are a well-known key topic in Distributed controlsystems. Most of the functionalities are implicitly based on the time consistency along the system. At the same time, general purpose operating systems, and Windows NT paradigmatically, have appeared in the control scene with undeniable strength. In fact, most of the SCADAs and industrial DCSs have migrated to this kind of platform. In this paper a clock synchronization protocol at driver level, based on the master/slave paradigm and using a dedicated and determinist channel, is presented and quantitative results are summarised. The time discrepancy results are applied to the clock correction at the slave by using a control algorithm. The given solution is based on a standard peripheral and so it can be considered as a benchmark result.
An integrated advanced control and supervision system in operation in a sugar factory is presented. The system works on top of a commercial distributed computer control system, and combines artificial intelligence tec...
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An integrated advanced control and supervision system in operation in a sugar factory is presented. The system works on top of a commercial distributed computer control system, and combines artificial intelligence techniques for fault detection and diagnosis with advanced predictive controllers and models for other tasks.
A method of automatically estimating the mitotic index of breast tissue samples is presented. The motivation for an automatic method is to minimise this time-consuming repetitive task demanded of experienced pathologi...
A method of automatically estimating the mitotic index of breast tissue samples is presented. The motivation for an automatic method is to minimise this time-consuming repetitive task demanded of experienced pathologists. The method used consists of two image processing stages which extract features that are suitable for pattern recognition. The final stage estimates the sample's mitotic index by combining the estimated probabilities of individual mitotic figures in the sample.
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