Currently, most commercial robot manipulators are equipped with conventional PID controllers due to their simplicity in structure and ease of design. Using such a controller, however, it is difficult to achieve a desi...
Currently, most commercial robot manipulators are equipped with conventional PID controllers due to their simplicity in structure and ease of design. Using such a controller, however, it is difficult to achieve a desired control performance since the dynamic equations of a mechanical manipulator are tightly coupled. In addition, they are highly nonlinear and uncertain. This paper uses a new hybrid control scheme to control a direct drive two-link manipulator under inertial parameters changes. The proposed hybrid control scheme consists of a fuzzy logic proportional controller and a conventional integral and derivative controller (FUZZY P+ID). In comparison with a conventional PID controller, only one additional parameter has to be adjusted to tune the FUZZY P+ID controller. The outlined experimental results demonstrate the effectiveness and the robustness of the new FUZZY P+ID controller.
The paper describes the design and implementation of a control system which in 1996 was successfully installed in a Slovenian brickworks. Its primary function is efficient control of the drying process in the factory,...
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The paper describes the design and implementation of a control system which in 1996 was successfully installed in a Slovenian brickworks. Its primary function is efficient control of the drying process in the factory, and so far this system is conceived as a classic computer-based process control system. With regard to the possible need to incorporate this control system into a future CIM information system, a concept of flexible recipes was applied as a possible integration link between planning, which is a typical business-level activity and process control, which is a production level activity. Flexible recipes thus may provide a modest contribution to the integration of shop floor control and logistical functions.
A case-study evaluation of a Wiener model based nonlinear predictive control method is presented. The approach makes use of Wiener model identification and does not require first-principles modelling. It was tested on...
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A case-study evaluation of a Wiener model based nonlinear predictive control method is presented. The approach makes use of Wiener model identification and does not require first-principles modelling. It was tested on a simulated model of a pH neutralisation process that was reconstructed from the literature. The obtained results are better than those resulting from the original physical model based nonlinear control and also of an artificial neural network (ANN) based approach. The performance is excellent also in the case of a considerable plant-to-model mismatch. There is a clear relation to the underlying linear model based method in a form of gain scheduling, so that the properties of the nonlinear control system can be analysed from the comprehensible linear control aspect. The method combines advantages of linear model based predictive control and gain scheduling while retaining a moderate level of computational complexity, thus it can be applied as the first next step in cases where performance of linear control is unsatisfactory due to process nonlinearity.
The paper addresses the problem of distinguishing between faults with the same fault signatures. It is shown that additional improvements in terms of resolution can be achieved if information about the sensitivity of ...
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The paper addresses the problem of distinguishing between faults with the same fault signatures. It is shown that additional improvements in terms of resolution can be achieved if information about the sensitivity of the residuals with respect to faults is taken into account. When two fault signatures are qualitatively identical but have significantly different sensitivity terms, additional discrimination can be achieved by using the ratios of the underlying residuals. This extra isolability feature simplifies reasoning in the isolation stage. However, to achieve better overall performance, the diagnostic results should be stable, i.e. should not vary substantially under different operating conditions. Improved diagnostic stability is obtained by the approximate reasoning approach which relies on the transferable belief model. An outline of the ideas is given and some practical results obtained on a DC motor are provided.
A dynamical mathematical model of a water supply plant based on lumped parameters is described. A concept of its control system is proposed that ensures output pressure stabilisation under conditions of variable water...
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A dynamical mathematical model of a water supply plant based on lumped parameters is described. A concept of its control system is proposed that ensures output pressure stabilisation under conditions of variable water consumption and variable water recourses. The control system consists of inner control loops which control the flow of each pump station and of a superimposed control loop that controls the output pressure of the water supply plant. The pressure controller calculates the cumulative reference value of the water flow for all controlled pumps and from this value an algorithm for the flow distribution calculates the reference flow for each inner loop, taking into account the level of water accumulation in each water well. control performances of output pressure obtained by a conventional PI controller and a fuzzy logic based controller are compared.
In order to apply a model based control strategy such as flexible recipes control to an industrial batch process, a model of the process dynamics is needed. This paper presents the modelling procedure for two such mod...
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In order to apply a model based control strategy such as flexible recipes control to an industrial batch process, a model of the process dynamics is needed. This paper presents the modelling procedure for two such models: a semi-empirical and an artificial neural network model. Both models predict precipitation rates of TiO 2 particles in an industrial hydrolysis process. Model properties and their prediction accuracy is compared. The artificial neural network is trained using the augmented training data set approach. A simulator has been designed to study the application Of flexible recipe instructions.
Process control systems are operated more or less in isolation from business systems relating to the same plant. As the potential benefits of integration have become clearer. there have been several attempts to link p...
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Process control systems are operated more or less in isolation from business systems relating to the same plant. As the potential benefits of integration have become clearer. there have been several attempts to link process control and business control systems. One aspect of linking is described in this paper. A primary function of a process control system, which was in 1996 successfully installed in a Slovenian brick/work, is efficient control of the drying process in the factory. and so far this system is conceived as classic computer-based process control systenl. With regard to the possible need to incorporate this control system into a future CIM information system, a concept of flexible recipes was applied as a possible integration link between planning. which is a typical business-level activity, and process control which is a production-level activity. Flexible recipes thus may provide a modest contribution to the integration of shop floor control and logistical functions.
A signed directed graph (SDG) model-based approach is given in this paper for fault diagnosis of process systems. The proposed method is modular, the model for fault propagation is built from the mini SDGs of the unit...
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A signed directed graph (SDG) model-based approach is given in this paper for fault diagnosis of process systems. The proposed method is modular, the model for fault propagation is built from the mini SDGs of the units driven by the process flowsheet. Thus the fault detection is decomposed into two steps: off-line generation of the SOG model and its rule set equivalent and the step of on-line fault detection.
Based on the concept of power converter fed machines (CFMs), high power density machines with nonsinusoidal current and back EMF waveforms are attracting more and more research interest. In this paper, a novel type of...
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Based on the concept of power converter fed machines (CFMs), high power density machines with nonsinusoidal current and back EMF waveforms are attracting more and more research interest. In this paper, a novel type of axial flux circumferential current permanent magnet (AFCC) machine topology is introduced. A sizing equation analysis, finite element analysis, optimization of parameters, performance simulation, details of the prototype and test data are included. In addition, a comparison of the power densities between the AFCC machine and the traditional induction machine based on the sizing and power density equations is also provided. Alternative manufacturing arrangements and the method to reduce torque ripple are discussed.
For very large document collections or high volume streams of documents, finding relevant documents is a major information filtering problem. One of the main types of information retrieval systems produces a word freq...
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For very large document collections or high volume streams of documents, finding relevant documents is a major information filtering problem. One of the main types of information retrieval systems produces a word frequency measure estimated by some important parts of the document using neural network approaches. This paper reports a new network structure for this task. It is specialised considering the main difficulties of these kinds of applications, namely, the calculation time complexity. It will be pointed out that the calculation, hence, the learning time is much reduced applying the new algorithm, however, the result is significantly improved compared to the former approaches, which offer a possibility to increase the number of considered words, hence, improve the effectiveness of information filtering systems.
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