We present numerical examples demonstrating the efficacy of a recently proposed self-triggered model predictive control scheme for disturbed linear discrete-time systems with hard constraints on the input and state. I...
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There have been numerous methods for learning and predicting time series ranging from the traditional time-series analyses to recent approaches using neural networks. A central issue common to all of them is the deter...
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There have been numerous methods for learning and predicting time series ranging from the traditional time-series analyses to recent approaches using neural networks. A central issue common to all of them is the determination of model structure. Both mean prediction error and An Information Criterion (AIC) are useful in model selection;the model with the smallest mean prediction error or AIC is selected from among a set of models as the best one. In this way they give a solution to the problem of model selection. Due to huge search space, however, the mean prediction error or AIC alone is not powerful enough to find the best model structure from among all the candidates. In the present paper the authors propose to use both a structural learning with forgetting and the mean prediction error or AIC to find a model with better generalization ability. Jordan networks and buffer networks, popular in the modeling of time series, are examined in this paper. The structural learning with forgetting and backpropagation (BP) learning are applied to compare the learning and prediction performance of these two types of models. Simulation results demonstrate that the structural learning with forgetting has better generalization ability than BP learning both in Jordan networks and buffer networks.
An approximate solution of the problem of linear-quadratic optimal control of the ground-induced vibrations of a vehicle travelling with variable velocity is presented. A new model in the form of a retarded functional...
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An approximate solution of the problem of linear-quadratic optimal control of the ground-induced vibrations of a vehicle travelling with variable velocity is presented. A new model in the form of a retarded functional differential equation is established which represents both vehicle dynamics and surface properties. By formulating the model in the spatial domain a number of technical difficulties are removed, and it is seen how constant spatial delays can be accommodated by using rational approximations. Equivalence between the space- and time-domain formulations is established, and an example demonstrating the viability of the approach is discussed.
The article presents the construction of an innovative electromagnetic mill, which in comparison to traditional solutions provide a significant reduction of energy consumption and higher technological performance. The...
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In this paper we study the inversion of the multidimensional Laplace transform by a combination of a general partial-fraction expansion formula and the theory of residues. The ideas may be applied to nonlinear systems...
In this paper we study the inversion of the multidimensional Laplace transform by a combination of a general partial-fraction expansion formula and the theory of residues. The ideas may be applied to nonlinear systems defined by Volterra series.
A good model is essential in simulating and analyzing a system satisfactorily. This paper proposes a new computer-aided modelling methodology to construct parsimonious models for dynamic physical systems. A set of dom...
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A good model is essential in simulating and analyzing a system satisfactorily. This paper proposes a new computer-aided modelling methodology to construct parsimonious models for dynamic physical systems. A set of domain-independent modelling principles and domain-dependent modelling constraints has been formulated to guide parsimonious model construction. Models and the knowledge base for the enhancement of models have been described by bond graphs. After a parsimonious model is generated, two types of qualitative analysis are conducted;one is to derive unknown states from known states and the other is to predict the effects of parameter changes on the whole system. This methodology is only applicable when the structure of a dynamic system is known beforehand. A detailed case study is presented to demonstrate this approach.
This paper proposes a RISC-V extension, named SigWavy, meant to optimize the PWM control for general purpose or application specific designs. The RISC-V extension named above is a PWM control Unit with a dedicated ISA...
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This paper presents theoretical and experimental investigations into modelling a single-link flexible manipulator system. An analytical model of the manipulator, characterised by an infinite number of modes, is develo...
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This paper presents theoretical and experimental investigations into modelling a single-link flexible manipulator system. An analytical model of the manipulator, characterised by an infinite number of modes, is developed using the Lagrange's equation and modal expansion method. This is used to develop equivalent time-domain and frequency-domain working models of the system in state-space and transfer function forms respectively. The model parameters are then estimated experimentally using system's measured input/output data. The model thus obtained is validated through experimentation and results including the effect of payload on system characteristics presented and discussed.
A new control system is described for the PUMA 560 industrial robotic manipulator based on transputer networks, where both the hardware and software designs are detailed. A Transputer Interface Board (TIE) establishin...
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A new control system is described for the PUMA 560 industrial robotic manipulator based on transputer networks, where both the hardware and software designs are detailed. A Transputer Interface Board (TIE) establishing a transputer link to the 6503 microprocessors of the PUMA arm joints has been designed, built and tested successfully. In addition to hardware implementation, software testing for this new system had been accomplished. The new system can communicate with the PUMA lower level controller at a much shorter period (i.e. 1.75 ms) than the default 28 ms. Genetic Algorithms are used to plan the PUMA robot minimum-time motion trajectory, which is not possible by the traditional exhaustive search method. Real-time experiments have been carried out based on the new PUMA control platform, and show a very good match with simulations. controlled by the new system, PUMA perfoms better when it is interfaced with the shorter time period. Copyright (C) 1996 Elsevier Science Ltd.
This paper presents an investigation into classifying myoelectric signals using a new fuzzy clustering neural network architecture for control of multifunction prostheses. Moreover, a comparative study of the classifi...
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