浅析我国热处理设备的更新换代

低真空变压热处理技术（包括设备和工艺）是综合低真空热处理和变压热处理的优点的专利技术。该技术的炉气能快速吐故纳新和精确调控,其炉温也能精确控制,且与真空热处理炉相比,其设备的价格也较低廉,是“老三炉”更新换代的理想产品。广泛采用低真空变压热处理技术是缩短我国同发达国家之间差距的捷径之一。     

基于深度学习的缓变故障早期诊断及寿命预测

为了克服传统的早期微小故障诊断方法不能区分多个不同时刻发生故障的不足,提出一种将深度学习和PCA相结合的方法实现微小缓变故障早期诊断及寿命预测。 对采集的数据进行深度学习实现逐层特征抽取,学习早期微小故障特征,建立微小缓变故障早期诊断模型,结合PCA方法将深度学习所抽取的高维故障特征向量集成为一个故障特征变量,根据历史故障数据特征变量演化规律定义数据驱动的故障演变标尺,并通过指数型非线性拟合方法建立寿命预测模型。 选取TE平台数据进行算法有效性检验,并与其他算法对比,从而验证了所提出算法的有效性。     

Influence diagnostics for multivariate GARCH processes

This article presents diagnostics for identifying influential observations when estimating multivariate generalized autoregressive conditional heteroscedasticity (GARCH) models. We derive influence diagnostics by introducing minor perturbations to the conditional variances and covariances. The derived diagnostics are applied to a bivariate GARCH model of daily returns of the S&P500 and IBM. We find that univariate diagnostic procedures may be unable to identify the influential observations in a multivariate model. Importantly, the proposed curvature‐based diagnostic identified influential observations where the correlation between the two series had a major change. These observations were not identified as influential using the univariate diagnostics for each asset separately. When estimating the bivariate GARCH model allowing for weights at influential observations, we found that the time‐varying correlations behaved differently from that implied by the model ignoring influential observations. The application therefore highlights the importance of extending univariate diagnostic procedures to multivariate settings.     

State controllability computation technique for linear time‐varying systems by using Taylor series approximation

This article presents a technique to determine the controllability Grammian matrix (CGM) for linear time‐varying systems by using truncated Taylor polynomial vector and the operational matrix of integration. An important property of this algorithm is that it starts by integrating the Lyapunov differential matrix equation in terms of the CGM. However, the algorithm does not use the mathematical integration processes actually, but uses the truncated Taylor polynomial vector and the operational matrix of integration. Thus, the problem is reduced to solving a linear set of algebraic equations with constant coefficients consisting of the Taylor polynomial constant coefficients of each of the CGM elements. Numerical results and error curves are given to illustrate the improvements achieved by the proposed algorithm. Copyright © 2008 John Wiley & Sons, Ltd.     

LMI OPTIMIZATION APPROACH FOR DELAY‐DEPENDENT H∞ CONTROL OF TIME‐VARYING DELAY SYSTEMS

In this paper, the robust delay‐dependent H_∞ control for a class of uncertain systems with time‐varying delay is considered. An improved state feedback H_∞ control is proposed to minimize the H_∞‐norm bound via the LMI optimization approach. Based on the proposed result, delay‐dependent criteria are obtained without using the model transformation technique or bounded inequalities on cross product terms. The linear matrix inequality (LMI) optimization approach is used to design the robust H_∞ state feedback control. Some numerical examples are given to illustrate the effectiveness of the approach.     

基于递推最小二乘支持向量回归估计的建模与预报

提出一种新的递推最小二乘支持向量回归估计算法（RLS-SVR），该算法具有实时性高、更新速度快的特点．充分应用RLS-SVR在线学习和训练的实时性，避免辨识模型的维数过高而降低估计精度，本文进一步提出了基于RLS-SVR的混合训练—估计辨识结构．TE过程的组分软测量建模和预报验证了该方法的有效性和优越性．     

Comments on: “Efficient robust constrained model predictive control with a time varying terminal constraint set” by Wan and Kothare

We present an algorithm that modifies the original formulation proposed in Wan and Kothare [Efficient robust constrained model predictive control with a time-varying terminal constraint set, Systems Control Lett. 48 (2003) 375–383]. The modified algorithm can be proved to be robustly stabilizing and preserves all the advantages of the original algorithm, thereby overcoming the limitation pointed out recently by Pluymers et al. [Min–max feedback MPC using a time-varying terminal constraint set and comments on “Efficient robust constrained model predictive control with a time-varying terminal constraint set”, Systems Control Lett. 54 (2005) 1143–1148].     

一种不确定离散时间系统的变结构控制方法

针对离散时间系统变结构控制中存在的问题,利用指数趋近律的趋近特性,提出一种新的离散变结构控制方法.利用递推估计的方法设计变结构控制律,有效地抵消了线性系统中慢变不确定性的影响,实现了对慢变非线性系统的控制.该方法克服了以往控制方法中需已知扰动上界的限制,降低了抖振,加快了趋近速度.仿真结果证明了该方法的有效性.     

A Trajectory-Based Approach for the Stability Robustness of Nonlinear Systems with Inputs

 We show, for two different definitions of semiglobal practical external stability, that the stability property holds on semi-infinite time intervals if and only if it holds on arbitrarily long but finite time intervals. These results have immediate applications in the analysis of the stability properties of highly oscillatory systems with inputs using averaging or for systems with inputs that are slowly varying. Results are stated for general flows and the stability is given with respect to arbitrary (not necessarily compact) sets. Date received: May 11, 2001. Date revised: March 14, 2002.     

Analysis of linear parameter‐varying systems using a non‐smooth dissipative systems framework

This paper presents new finite‐dimensional linear matrix inequality formulations for several important analysis problems of linear parameter‐varying systems. The approach is based on a non‐smooth dissipative systems framework using a continuous, piecewise‐affine parameter‐dependent Lyapunov function. The new analysis approach yields guaranteed and less conservative results than previously published techniques that are based on affine parameter‐dependent Lyapunov functions or Luré–Postnikov Lyapunov functions. Conservatism is reduced in this new approach because the analysis uses a more general class of parameter‐dependent Lyapunov functions (PDLFs). The new approach also provides an explicit trade‐off between conservatism and computational effort of the analysis technique. Note that, in contrast to the gridding approach typically used to develop a computationally feasible algorithm, this proposed approach guarantees the analysis results. This paper also shows that the numerical results of our approach, while computationally intensive, could be used to develop many new insights into the selection of PDLFs in the other analysis techniques. Copyright © 2002 John Wiley & Sons, Ltd.