This paper presents an investigation into the performance evaluation of homogeneous and heterogeneous parallel architectures in the real-time implementation of finite element (FE) simulation algorithm of a flexible ma...
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This paper presents an investigation into the performance evaluation of homogeneous and heterogeneous parallel architectures in the real-time implementation of finite element (FE) simulation algorithm of a flexible manipulator. The algorithm is implemented on a number of homogeneous and heterogeneous architectures incorporating high-performance processors. The partitioning and mapping of the algorithms on both the homogeneous and heterogeneous architectures are investigated and finally a comparative assessment of the performance of the architectures in implementing the algorithm revealing the capabilities of the architectures in relation to the nature of the algorithm is presented in terms of execution time and speedup.
The derivations of orthogonal least-squares algorithms based on the principle of Hsia's method and generalized least-squares are presented. Extensions to the case of non-linear stochastic systems are discussed and...
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The derivations of orthogonal least-squares algorithms based on the principle of Hsia's method and generalized least-squares are presented. Extensions to the case of non-linear stochastic systems are discussed and the performance of the algorithms is illustrated with the identification of both simulated systems and linear models of an electric arc furnace and a gas furnace.
The performance demands in modern signal processing and control applications have motivated a trend towards utilisation of complex algorithms. This, in turn, has resulted in a resurgence in the development of high per...
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The performance demands in modern signal processing and control applications have motivated a trend towards utilisation of complex algorithms. This, in turn, has resulted in a resurgence in the development of high performance systems to make the real-time realisation of such algorithms feasible in practice. This paper presents an investigation into the performance of sequential architectures/uni-processor based systems in the real-time implementation of finite element algorithm of a flexible manipulator. The algorithm is implemented on a number of high-performance processors. A comparative assessment of the performance of the processors in implementing the algorithm, revealing the capabilities of the processors in relation to the nature of the algorithm, is presented in terms of execution time and speedup. The effect of compiler optimisation facilities on the execution time in implementing the algorithm is also demonstrated.
This paper presents the development of a neuro-adaptive active noise control (ANC) system. Radial basis function neural networks with an orthogonal forward regression algorithm are considered in both the modelling and...
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This paper presents the development of a neuro-adaptive active noise control (ANC) system. Radial basis function neural networks with an orthogonal forward regression algorithm are considered in both the modelling and control contexts. A feedforward ANC structure is considered for optimum cancellation of broadband noise in a three-dimensional propagation medium. An on-line adaptation and training mechanism allowing a neural-network architecture to characterise the optimal controller within the ANC system is developed. The neuro-adaptive ANC algorithm thus developed is implemented within a free-field environment,and simulation results verifying its performance are presented and discussed. Copyright (C) 1997 Elsevier Science Ltd.
This paper describes a binary image representation scheme, called Image Block Representation and presents new algorithms for a number of basic binary image processing and analysis operations, which are rapidly impleme...
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This paper describes a binary image representation scheme, called Image Block Representation and presents new algorithms for a number of basic binary image processing and analysis operations, which are rapidly implemented on block-represented binary images. The main purpose of the Image Block Representation is to provide an efficient binary image representation that permits the execution of operations on image areas instead of image points.
Correlation-based model validity tests are introduced to monitor the operation of non-linear adaptive noise cancellation filters and to detect whether the filters are operating correctly or incorrectly. The tests are ...
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Correlation-based model validity tests are introduced to monitor the operation of non-linear adaptive noise cancellation filters and to detect whether the filters are operating correctly or incorrectly. The tests are derived for a NARMAX (Non-linear Autor-Regressive Moving Average model with eXogenous inputs) filter design based on a Sub-Optimal Least Squares (SOLS) estimation algorithm. Simulation studies are included to illustrate the performance of the new tests.
Decentralized adaptive control schemes using the principle of dominant subsystems are presented for time-varying nonlinear dynamic large-scale interconnected systems. Sufficient conditions for the existence of local d...
Decentralized adaptive control schemes using the principle of dominant subsystems are presented for time-varying nonlinear dynamic large-scale interconnected systems. Sufficient conditions for the existence of local decentralized adaptive control laws stabilizing a given large-scale system (LSS) are derived in terms of controller parameters for incompletely known composite systems. The approach proposed in this paper is applied to nonlinear stabilizing adaptive decentralized control (ADC) of multimachine power systems. The stability of the multimachine power systems with the ADC is illustrated by the simulation results for a two machine system.
This paper develops and investigates a dual unscented Kalman filter (DUKF) for the joint nonlinear state and parameter identification of commercial adaptive cruise control (ACC) systems. Although the core functionalit...
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This paper presents the evolution of controlsystems and trends in the field of integrated computer, communication and cognitive sciences for control applications. There have been selected and presented the most effic...
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This paper presents the evolution of controlsystems and trends in the field of integrated computer, communication and cognitive sciences for control applications. There have been selected and presented the most efficient control strategies used in complex process control, as well as the limitations of model-based approaches in cases that imply complex, non-linear and uncertain process models. In this context, the paper presents some trends in robust identification and design of adaptive controlsystems with a high level of robustness. Concepts for autonomous control of complex systems by the integration of intelligent methodologies are analyzed. Some aspects of hybrid intelligent control are considered and new directions of research towards creating a new generation of controlsystems are presented. The paper also includes a review of the evolution of computer controlled applications and a new paradigm - C4- is analyzed from concept to application. Therefore, the transition from C2to C4paradigm is illustrated in the context of integrating computers, communication and cognition in control. Finally, advanced control techniques for manufacturing are presented, including intelligent agents, leading to large Intelligent Manufacturing systems. Some trends in the control of complex systems are presented, including multi-agent technology and hybrid systems formalism.
We investigate the evolutionary Prisoner's Dilemma and the Snowdrift Game on small-world networks in a realistic social context where individuals consider their local contributions to their group and update their ...
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We investigate the evolutionary Prisoner's Dilemma and the Snowdrift Game on small-world networks in a realistic social context where individuals consider their local contributions to their group and update their strategies by self-questioning. An individual with introspection can determine whether its current strategy is superior by playing a virtual round of the game and its local contribution is defined as the sum of all the payoffs its neighbors collect against it. In our model, the performance of an individual is determined by both its payoff and local contribution through a linear combination. We demonstrate that the present mechanism can produce very robust cooperative behavior in both games. Furthermore, we provide theoretical analysis based on mean-field approximation, and find that the analytical predictions are qualitatively consistent with the simulation results.
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