Object-oriented database systems aim at meeting the data modelling, performance, cooperative design and version management requirements of current advanced applications, such as CAD (computer-aided design), CAM (compu...
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Object-oriented database systems aim at meeting the data modelling, performance, cooperative design and version management requirements of current advanced applications, such as CAD (computer-aided design), CAM (computer-aided manufacturing), CASE (computer-aided software engineering), CIM (computer integrated manufacturing), hypermedia and expert systems. This paper presents the ALEX Object Manager, which is a part of the ALEX object-oriented database management system that is being developed based on the ODMG-93 standard. The system decomposition and process layout are presented, some implementation problems are discussed and the current status of the system is reported.
This paper presents a model-based approach to fault detection of dynamic systems, which is robust to unmodeled dynamics. A “Quasi-ARMAX model᾿ is first proposed for describing nonlinear systems by incorporating a gro...
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This paper presents a model-based approach to fault detection of dynamic systems, which is robust to unmodeled dynamics. A “Quasi-ARMAX model᾿ is first proposed for describing nonlinear systems by incorporating a group of certain nonlinear structures into a linear ARMAX structure. The model can be used for a best linear approximation of the system, as well as for the estimation of resulting unmodeled dynamics, by a hierarchical implementation of recursive identification. Then robust fault detection is performed based on thresholding approach using Kullback discrimination information as fault detection index, in which the estimated unmodeled dynamics is incorporated.
This research is concerned with fault detection of nonlinear systems using Kullback discrimination information (KDI) as an index. A hybrid quasi-ARMAX model is proposed, which combines a linear ARMAX model and a multi...
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This research is concerned with fault detection of nonlinear systems using Kullback discrimination information (KDI) as an index. A hybrid quasi-ARMAX model is proposed, which combines a linear ARMAX model and a multi-ARX-model based on interpolation. In the case where the faults occur on the ARMAX model part, a KDI-based "robust" fault detection is performed, in which multi-ARX-model part is treated as error due to nonlinear undermodeling. In other cases, the model is transformed into several local ARMAX models and fault detection is performed by using the KDI to discriminate each identified local model. In this paper, we mainly concentrate our discussion on the latter cases.
In the paper a continuous-time approach to parameter estimation of continuous-time systems is addressed. A linear continuous-time single-input single-output system model described by means of a transfer function is ta...
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In the paper a continuous-time approach to parameter estimation of continuous-time systems is addressed. A linear continuous-time single-input single-output system model described by means of a transfer function is taken into consideration. A weighted quadratic criterion function, which defines the quality of the estimation process, the resulting least-squares algorithm and its characteristics are expressed in the continuous-time domain. In order to accommodate the continuous-time design to the discrete-time domain, various numerical methods are proposed. Simulation results that illustrate the performance of the proposed methods are presented and discussed.
The paper indicates an analytic computing relation for the solution to Riccati differential matrix equation and -based on that- it establishes the weight matrices influence on the solution of the equation and on the L...
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The paper indicates an analytic computing relation for the solution to Riccati differential matrix equation and -based on that- it establishes the weight matrices influence on the solution of the equation and on the LQ-Problem’s criterion minimum value either. It indicates also an efficient way for the optimal controller implementation.
This paper presents a robust fault detection system (FDS) for dynamic systems with unmodeled dynamics. In the FDS, umnodeled dynamics is first qualified as soft bound, which as well as model parameters are estimated u...
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This paper presents a robust fault detection system (FDS) for dynamic systems with unmodeled dynamics. In the FDS, umnodeled dynamics is first qualified as soft bound, which as well as model parameters are estimated using a robust identification algorithm. Then as a fault detection index, Kullback discrimination information (KDI) is derived into a feasible form and an index of umnodeled dynamics is also introduced. A decision making scheme is thus developed so that fault detection is carried out based on the KDI, the index of umnodeled dynamics and other prior information about the system.
At the preparatory stage for connecting the Czech power systems to the West European UCPTE system, corrections for frequency must be included in the output power control, i.e. the primary control must be introduced. T...
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At the preparatory stage for connecting the Czech power systems to the West European UCPTE system, corrections for frequency must be included in the output power control, i.e. the primary control must be introduced. The result of the detailed analysis was a model of primary output power control of the block and a new power system control of Czech coal power plants. In the new power system control, an adaptive or robust controller will be used for operation stabilisation
In this article a multimedia computer-assisted learning (MCAL) system is presented. The major objective of this work was to investigate the potential of using such systems as tools for transferring instructional cours...
In this article a multimedia computer-assisted learning (MCAL) system is presented. The major objective of this work was to investigate the potential of using such systems as tools for transferring instructional course information through various types of computer media as opposed to the classic CAL systems. The philosophy and techniques employed to design the system are investigated. Usage of the implemented system and its merits have been illustrated through its application to teach engineering students and technicians the theory and concepts of marine radar. System design, implementation, test, and revision phases are presented and discussed.
In this paper, a combined method of change detection and failure decision is proposed for the system under the adaptive control based on the self-tuning regulator. The controlled system is assumed encounter unexpected...
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In this paper, a combined method of change detection and failure decision is proposed for the system under the adaptive control based on the self-tuning regulator. The controlled system is assumed encounter unexpected parameter changes, which may be caused by a failure or a normal operation. Such a system change can effectively be detected by using Fullback Discrimination Information (KDI) as an index for model discrimination. In order to decide whether the detected system change is caused by a failure or not, a neural network approach to failure decision is introduced. Based on the knowledge about failure modes and system operations, the regulator parameter variations after the change detection are used as training data for the network learning. In this way an on-line monitoring scheme of adaptively controlled systems can be established. Simulation studies of a second-order damped oscillator have been earned out to demonstrate the effectiveness of the method.
An on-line scheme to failure diagnosis is proposed for dynamic systems under adaptive control, which is designed based on a direct approach to self-tuning regulator. Failure modes occurred in the system are assumed to...
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An on-line scheme to failure diagnosis is proposed for dynamic systems under adaptive control, which is designed based on a direct approach to self-tuning regulator. Failure modes occurred in the system are assumed to be described by unexpected changes in physical parameters of the system. The parameter changes in the controlled system can effectively be detected by using Kullback Discrimination Information (KDI) as an index for model discrimination. In order to decide whether the detected system parameter change is caused by a failure or not, a fuzzy inference approach to failure decision is considered. Some appropriate membership functions which describe fuzzy events of failures are constructed to perform the fuzzy inference. In this way, useful knowledge about failure modes which is available from, e.g., experts can be introduced into the model- based diagnosis technique. Simulation studies of a second-order damped oscillator have been carried out to demonstrate the effectiveness of the method.
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