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SICE '95. Proceedings of the 34th SICE Annual Conference. International Session Papers最新文献

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A MULTINEURO computer system by using high performance digital neuro processor 采用高性能数字神经处理器的multiineuro计算机系统
T. Saito, Y. Baba, K. Nakagawa, Y. Fuwa, Y. Shimokawa
We have developed an accelerator device "MULTINEURO-A" which incorporates multiple processors (one master node and plural slave nodes) dedicated to neural network high-speed computing realized on an engineering workstation. Nodes are connected by two data paths, broadcast bus and ring bus. Processing speed is in proportion to the number of processors. It is built in two boards (master and slave) having 64 VLSI processors that offers to 1.5 billion connections per seconds. It processes forward/backward calculation of multilayer perceptron type neural networks, feedback type neural networks such as Hopfield model, and any other types by programming for parallel processing.
我们开发了一种集成了多个处理器(一个主节点和多个从节点)的加速装置“multi - euroa”,用于在工程工作站上实现神经网络高速计算。节点之间通过广播总线和环形总线两条数据路径连接。处理速度与处理器的数量成正比。它内置在两块板(主板和从板)上,拥有64个VLSI处理器,每秒提供15亿个连接。它通过编程并行处理多层感知器型神经网络、反馈型神经网络(如Hopfield模型)和任何其他类型的神经网络的前向/后向计算。
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引用次数: 0
A stabilizing controller for multirate sampled-data systems 多速率采样数据系统的稳定控制器
Young Baek Kim, Sang Jeong Lee
Designs a multirate controller for a given multirate sampled-data system which has a periodic output measurement scheme. A sufficient condition for maintaining observability in multirate sampled-data systems is given first. The design strategy for disturbance rejection is proposed. The proposed controller has IMC structure, and can be decomposed into a disturbance estimator and the inverse of the fast plant. The authors assume that the disturbance consists of a sum of finite number of sine waves with different frequencies and DC bias. Simple examples are presented for illustrations.
针对给定的具有周期性输出测量方案的多速率采样数据系统,设计了一种多速率控制器。首先给出了多速率采样数据系统保持可观测性的一个充分条件。提出了抗干扰设计策略。该控制器具有内模控制结构,可分解为扰动估计器和快速对象的逆。作者假设扰动由有限个不同频率的正弦波和直流偏置组成。举了一些简单的例子来说明。
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引用次数: 0
Controller design using parametric neural networks 采用参数化神经网络设计控制器
M. Hasheminejad, J. Murata, K. Hirasawa
A neural network (NN) of a more flexible internal structure than usual is used to design a better controller. A parametric NN (PNN) can represent both linear and nonlinear relationships explicitly and simultaneously by setting its parameters appropriately. In many cases we have some information about the system which enable us to build a linear controller for it. But of course this is not enough for treating nonlinear plants. Using PNN we could make a complimentary linearized controller and then, after starting the learning, in an online manner it will be extended to a nonlinear dominant controller.
采用一种内部结构更灵活的神经网络来设计更好的控制器。参数神经网络(PNN)通过适当设置参数,可以同时明确地表示线性和非线性关系。在许多情况下,我们有一些关于系统的信息,使我们能够为它建立一个线性控制器。当然,这对于处理非线性植物是不够的。使用PNN,我们可以制作一个互补的线性化控制器,然后,在开始学习后,以在线的方式将其扩展为非线性主导控制器。
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引用次数: 1
Identification of nonlinear systems based on adaptive fuzzy systems embedding quasi-ARMAX model 基于自适应模糊系统嵌入准armax模型的非线性系统辨识
Jinglu Hu, K. Kumamaru
This paper addresses the issues related to identification of nonlinear systems based on adaptive fuzzy systems (AFSs) embedding quasi-ARMAX model. A general nonlinear system can be represented as a quasi-ARMAX form, in which the parameters .
本文研究了基于自适应模糊系统(afs)嵌入准armax模型的非线性系统辨识问题。一般非线性系统可以表示为拟armax形式,其中参数。
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引用次数: 2
On the stability of controllers for self-sensing magnetic bearings 自感磁轴承控制器的稳定性研究
T. Mizuno, K. Araki, H. Bleuler
A comparison between the controllers using a full-order observer and the reduced-order observer are made from the viewpoint of strong stabilization in self-sensing active magnetic bearings. It is shown that any reduced-order observer based controller stabilizing the plant is unstable while full-order observer based controllers are stable. The self-sensing suspension in magnetic bearings with solid cores is also discussed. It is shown that the controllers are destabilized by a modification of the eddy currents flowing through the cores. It gives the reason for the difficulty of actual self-sensing suspension in the solid-cored magnetic bearing.
从自感知主动磁轴承的强镇定角度出发,比较了采用全阶观测器和降阶观测器的控制器。证明了镇定对象的任何基于降阶观测器的控制器都是不稳定的,而基于全阶观测器的控制器是稳定的。讨论了实心磁轴承的自传感悬架。结果表明,通过改变流过磁芯的涡流会使控制器失稳。给出了在实心磁轴承中实现自感悬浮困难的原因。
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引用次数: 5
On-line self tuning fuzzy controller using intelligent membership function 采用智能隶属函数的在线自整定模糊控制器
Seok-Yong Oh, Dong-Jo Park
A new design method is proposed for a fuzzy logic controller (FLC). By analyzing phase plane characteristics we can build and optimize the rule base of FLC. Variation of universe of discourse (UOD) can give coarse or fine control effects. With this variable UOD an adaptive gain tuning method is used to improve performance in transient and steady state. To show the improved performance of FLC and effectiveness of these methodologies, it is applied to design of attitude control system for a flexible spacecraft which has inherently a strong nonlinearities such as a hysteresis and a dead band.
提出了一种新的模糊控制器(FLC)设计方法。通过对相平面特性的分析,可以建立和优化FLC的规则库。变异语域可以实现粗、精两种控制效果。利用可变UOD,采用自适应增益调谐方法提高了暂态和稳态性能。为了证明FLC的改进性能和这些方法的有效性,将其应用于具有滞回和死区等强非线性特性的柔性航天器姿态控制系统的设计。
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引用次数: 7
Serial failure diagnosis of computer system by Petri net 基于Petri网的计算机系统串行故障诊断
M. Katsumata, M. Kurihara, A. Ohuchi, Y. Sugasawa
Network technologies have rapidly developed and distributed computer control systems which are of asynchronous and parallel characteristics are very useful in various fields. However, it is very difficult to figure out the factors of failure of such systems. In this paper, we make a Petri net model of a simple distributed computer control system consisting of a main system and a subsystem, and show how to diagnose serial failure of the system by analyzing invariant sets of the model.
随着网络技术的迅速发展,具有异步和并行特性的分布式计算机控制系统在各个领域得到了广泛应用。然而,要找出这类系统的失效因素是非常困难的。本文建立了一个由主系统和子系统组成的简单分布式计算机控制系统的Petri网模型,并通过分析模型的不变量集来诊断系统的系列故障。
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引用次数: 2
Design of H/sub /spl infin// controller for precise positioning system 精密定位系统H/sub /spl / in//控制器的设计
A. Yamauchi, T. Murakami, A. Morán, M. Hayase
The control system of a positioning mechanism with resonance and Coulomb friction has been designed using H/sub /spl infin// control theory, and the control performance has been verified by computer simulation and experimental analysis. DGKF type H/sub /spl infin// control with scalar weighting factors and GD type H/sub /spl infin// control with frequency-dependent weighting function based on integral action were utilized for designing the control system. The followings have been confirmed from this study: (1) H/sub /spl infin// control has good robustness properties for a wide range of operating conditions in the presence of external disturbances such as Coulomb friction. (2) DGKF type H/sub /spl infin// controller presents better convergence and robustness properties than GD type H/sub /spl infin// controller.
采用H/sub /spl / infin//控制理论,设计了具有共振和库仑摩擦的定位机构控制系统,并通过计算机仿真和实验分析验证了其控制性能。采用标量加权因子DGKF型H/sub /spl infin//控制和基于积分作用的频率相关加权函数GD型H/sub /spl infin//控制进行控制系统设计。研究结果表明:(1)H/sub /spl / in//控制在库仑摩擦等外部扰动存在的大范围工况下具有良好的鲁棒性。(2) DGKF型H/sub /spl infin//控制器比GD型H/sub /spl infin//控制器具有更好的收敛性和鲁棒性。
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引用次数: 0
Feedback linearization for SMA (shape memory alloy) 形状记忆合金的反馈线性化
K. Arai, S. Aramaki, K. Yanagisawa
The problem of the SMA (shape memory alloy) which is appropriate actuator for micromanipulator is its hysteresis characteristic. To get a high controllability of SMA, feedback linearization method that is based on the continuous modeling of SMA was applied. As the result easily designed nonlinear feedback system was achieved. Furthermore, this control method was applied to the control of two-link SMA micromanipulator and /spl plusmn/0.5 mm positioning accuracy was achieved.
形状记忆合金的滞回特性是其适合用于微机械臂作动器的问题。为了获得SMA的高可控性,采用了基于SMA连续建模的反馈线性化方法。结果表明,设计非线性反馈系统非常容易。将该控制方法应用于双连杆SMA微机械臂的控制,实现了/spl plusmn/0.5 mm的定位精度。
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引用次数: 25
A learning method of multilayer neural networks for pruning hidden units 一种多层神经网络的隐单元修剪学习方法
H. Takechi, K. Murakami
This paper presents a learning method of multilayer neural networks for pruning hidden units. In this method, the learning rates of each unit are adaptively changed to unbalance the influence of the hidden units on the network. With this method, useless hidden units are easily found and networks with small number of hidden units are constructed.
提出了一种多层神经网络的隐单元修剪学习方法。该方法自适应地改变每个单元的学习率,以平衡隐藏单元对网络的影响。利用该方法可以很容易地找到无用的隐藏单元,并构造具有少量隐藏单元的网络。
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引用次数: 0
期刊
SICE '95. Proceedings of the 34th SICE Annual Conference. International Session Papers
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