The paper presents a new approach to reconstruction of audio signals. First, a general reconstruction formula is derived allowing one to estimate unknown samples from the known (neighboring) ones. Then it is shown tha...
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The paper presents a new approach to reconstruction of audio signals. First, a general reconstruction formula is derived allowing one to estimate unknown samples from the known (neighboring) ones. Then it is shown that the unknown excitation appearing in the analytical reconstruction formula can be replaced with the natural excitation waveform extracted from the available portions of the signal.
In this paper, an adaptive decentralized controller is presented to attenuate the transversal vibration of a flexible cablestayed bridge induced by seismic excitation, in which only local sensor information has been u...
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The main objective of this contribution is a new development of the continuous-time generalised predictive control (CGPC) resulting in a Youla-based CGPC design procedure for both minimumphase and nonminimum-phase unc...
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The main objective of this contribution is a new development of the continuous-time generalised predictive control (CGPC) resulting in a Youla-based CGPC design procedure for both minimumphase and nonminimum-phase uncertain SISO systems. The derived design procedure consists of two steps. In the first step nominal stability and nominal performance of the control system are established by using a fully analytical design methodology, based on a collection of closed-loop prototype characteristics with definite time-domain specifications. In the second step, the primary structure of the CGPC controller is suitably enriched by `Youla' blocks guaranteeing that the resulting CGPC control system has the required robustness properties, i.e. robust stability and robust performance.
Static task scheduling in distributed computing systems is a very complex problem and known to be NP-hard. This problem is even harder when the module execution times become probabilistic. In this paper we study the e...
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Static task scheduling in distributed computing systems is a very complex problem and known to be NP-hard. This problem is even harder when the module execution times become probabilistic. In this paper we study the effect of probabilistic module execution times on the performance of task-scheduling algorithms. We show that in static task scheduling, for probabilistic module execution times, and in the existence of some factors there is no need to use an expensive task-scheduling algorithm. Given any two static task-scheduling algorithms that use deterministic module execution times in assigning task modules to the distributed system, the performance of these two algorithms will not remain the same when these module execution times become probabilistic rather than deterministic. We also study the effects of some factors an our results.
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.
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