This paper introduces the architecture of a virtual machine designed to play Grafcet models. The architecture proposed is highly flexible and can be used to implement different types of Grafcet players. In addition, m...
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This paper introduces the architecture of a virtual machine designed to play Grafcet models. The architecture proposed is highly flexible and can be used to implement different types of Grafcet players. In addition, many of the variable aspects considered when playing a Grafcet can be completely redefined, even changed dynamically. An object-oriented static meta-model for the Grafcet language is also introduced.
The cell formation problem is a classic manufacturing optimisation problem associated with the implementation of a cellular manufacturing system. A variety of hierarchical clustering procedures have been proposed for ...
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The cell formation problem is a classic manufacturing optimisation problem associated with the implementation of a cellular manufacturing system. A variety of hierarchical clustering procedures have been proposed for the solution of this problem. Essential for the operation of a clustering procedure is the determination of a form of similarity between the objects that are going to be grouped. The authors employ a genetic programming algorithm for the evolution of new similarity coefficients for the solution of simple cell formation problems. Evolved coefficients are tested against the well-known Jaccard's similarity coefficient on a large number of problems taken from the literature.
This paper presents an interface for the interaction between a human and an adapted kitchen where different elements, including a robot, have to be controlled. After the global structure of the interface is described ...
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This paper presents an interface for the interaction between a human and an adapted kitchen where different elements, including a robot, have to be controlled. After the global structure of the interface is described a more detailed explanation is presented on the way the interface offers the user an easy and friendly way to select the desired objects and to provide their position to the robot for their manipulation.
Proposes a method to reconstruct acoustic signals from auditory nerve firings. This is a major step in order to improve cochlear implants by demonstrating what patients perceive with such a device. A computer model of...
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Proposes a method to reconstruct acoustic signals from auditory nerve firings. This is a major step in order to improve cochlear implants by demonstrating what patients perceive with such a device. A computer model of the human cochlea transforms an acoustic test signal into a train of impulses, and the place- and volley-principle of cochlear frequency coding will be evaluated in order to invert this process, i.e. to reconstruct the original signal from the impulses. Phase-locking of the impulses to an acoustic stimulus is believed to be the main information carrier of loudness and frequency in the cochlea. Four different synchronization indices, which are used to assess phase-locking in the sensory receptor cells of the ear, will be presented and compared.
This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of ...
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This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of the surface of 3-D objects with a multi-objective optimization function to meet the needs of a wide range of applications. Further, a new crossover operator for triangulation and a new 3-D quadrilateral mutation operator are also introduced.
This paper presents theory, algorithms and validation results for system identification of continuous-time state-space models from finite input-output sequences. The algorithms developed are methods of subspace model ...
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This paper examines the potential for using empirical models derived from real plant data for online quality control for an enamelled wire production process. Existing procedures are based around a well-established of...
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This paper examines the potential for using empirical models derived from real plant data for online quality control for an enamelled wire production process. Existing procedures are based around a well-established offline technique known as Tangent Delta. Using data recorded from normal production operations, models representing parameter input/output relationships are fast developed using standard linear regression. The linear models do not capture the behaviour of the process sufficiently well so other methods based on nonlinear and fuzzy methods and artificial neural networks are developed. The ability of each of these methods to capture the process characteristics are compared using test set data. The results indicate that the nonlinear models derived using the group method of data handling (GMDH) approach offer considerable promise for online quality control in this industrial application.
Maximum likelihood estimation of single-input single-output linear time-invariant dynamic models requires that the model innovation (the nonmeasurable white noise source that is assumed to be the source of the randomn...
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Maximum likelihood estimation of single-input single-output linear time-invariant dynamic models requires that the model innovation (the nonmeasurable white noise source that is assumed to be the source of the randomness of the system) can be computed from the observed data. For many model structures, the prediction error and the model innovation coincide and the prediction error can be used in maximum likelihood estimation. However, when the model dynamics and the noise model have unstable poles which are not shared or when the noise dynamics have unstable zeros this is not the case. One such example is an unstable output error model. In this contribution we show that in this situation the model innovation can be computed by noncausal filtering. Different implementations of the model innovation filter are also studied.
In this note we consider the problem of H ∞ observer design for a class of uncertain linear discrete-time systems with delayed state and parameter uncertainties. The goal of this problem is to design a linear state o...
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In this note we consider the problem of H ∞ observer design for a class of uncertain linear discrete-time systems with delayed state and parameter uncertainties. The goal of this problem is to design a linear state observer such that, for the positive integer state time-delay and all admissible norm-bounded parameter uncertainties, the observation process remains robustly stable and the transfer function from exogenous disturbances to error state outputs meets the prespecified H ∞ norm upper bound constraint. The observer structure does not depend on the parameter uncertainties. A simple, effective algebraic methodology is developed to derive the conditions for the existence of the desired robust H ∞ observers, and the analytical expression of these observers is then characterized in terms of the matrix Riccati-like equations/inequalities. We provide a numerical example to demonstrate the validity and the applicability of the proposed approach.
This note deals with the problem of H ∞ observer design for a class of uncertain linear systems with delayed state and parameter uncertainties. This problem aims at designing the linear state observers such that, for...
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This note deals with the problem of H ∞ observer design for a class of uncertain linear systems with delayed state and parameter uncertainties. This problem aims at designing the linear state observers such that, for all admissible parameter uncertainties, the observation process remains robustly stable and the transfer function from exogenous disturbances to error state outputs meets the prespecified H ∞ on norm upper bound constraint, independently of the time-delay. The time-delay is assumed to be small but unknown, and the parameter uncertainties are allowed to be norm-bounded and appear in all the matrices of the state-space model. An effective matrix inequality methodology is developed to solve the proposed problem. We derive the conditions for the existence of the desired robust H ∞ observers, and then characterize the analytical expression of these observers. A numerical example demonstrates the validity and applicability of the present approach.
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