求解工程结构优化问题的改进布谷鸟搜索算法

针对布谷鸟搜索算法局部搜索能力不强的缺点, 提出一种基于随机局部搜索的改进布谷鸟搜索算法用于求解工程结构优化问题。引入惯性权重以平衡算法的勘探和开采能力; 利用随机局部搜索方法对当前最优解进行局部搜索, 以加快算法的收敛速度。两个工程结构优化问题的实验结果表明了该算法的可行性和有效性。     

可逆冷带轧机速度张力多变量耦合系统的建模及分散控制

针对具有多变量、非线性、强耦合和不确定性的可逆冷带轧机速度张力系统,提出了一种基于扩张状态观测器(extended state observer,ESO)的全局积分滑模自适应反步分散控制方法.首先,采用机理建模方法,建立了相对完备的可逆冷带轧机速度张力多变量耦合系统的数学模型.其次,将各子系统的耦合项和不确定项看成外扰,通过构造的ESO对其进行动态观测,并分别引入所设计的全局积分滑模自适应反步控制器中进行补偿,速度张力系统实现了有效的动态解耦和协调控制.理论分析表明,所提出的控制方法能够保证滑模面的渐近稳定和闭环系统的渐近跟踪性能.最后,基于某1422mm可逆冷带轧机速度张力系统的实际数据进行仿真,结果验证了所提方法的有效性.     

具有数据包丢失的离散随机不确定系统的线性最优满阶估值器

研究了具有数据包丢失和随机不确定性离散随机线性系统的状态估计问题.其中数据包丢失是随机的,且满足Bernoulli分布,系统矩阵中的随机不确定性由一个白色乘性噪声来描述.首先,通过配方方法,提出了最小均方意义下的无偏最优线性递推满阶滤波器.所提出的滤波器用到了当前时刻和最近时刻接收到的观测来保证线性最优性.与多项式滤波和增广滤波器相比,本文的滤波器具有较小的计算负担.然后,基于所获得的线性滤波器推导了线性最优预报器和平滑器.进一步研究了线性最优估值器的渐近稳定性,给出了稳态特性存在的一个充分条件.最后,通过两个仿真例子验证了所提估计算法的优越性.     

On a Mixture GARCH Time‐Series Model

Abstract. Recently, there has been a lot of interest in modelling real data with a heavy‐tailed distribution. A popular candidate is the so‐called generalized autoregressive conditional heteroscedastic (GARCH) model. Unfortunately, the tails of GARCH models are not thick enough in some applications. In this paper, we propose a mixture generalized autoregressive conditional heteroscedastic (MGARCH) model. The stationarity conditions and the tail behaviour of the MGARCH model are studied. It is shown that MGARCH models have tails thicker than those of the associated GARCH models. Therefore, the MGARCH models are more capable of capturing the heavy‐tailed features in real data. Some real examples illustrate the results.     

随机时变路网下的城市应急服务车辆路径分析

针对城市应急服务车辆（110、119、120等）的最优路径选择问题及路网的随机性与时变性,利用鲁棒优化理论,考虑路网在最坏情况下的行程时间,建立了随机时变条件下的应急车辆路径选择模型,并对 Dijkstra算法进行改进,将算法的路阻矩阵进行实时更新,以在时变条件下实现对路径选择模型的求解。经算例分析表明,该模型能有效解决随机时变路网环境下的应急车辆最优路径问题,与基于概率分布的期望行程时间最短的方法相比,该模型拥有更高的鲁棒性和易操作性。     

BELL整体比例调节型电动执行机构的电路连接与调试方法

天津贝尔自动化仪表技术有限公司引进法国先进技术,生产的电动执行机构广泛用于自动控制系统。新一代“卓越引进系列”具有多种保护功能和多种控制方式,更适宜现代工控需求。在百种以上规格中,搞清楚最基本类型——标准整体比例调节型是其他类型的基础。文章结合厂家提供的资料,针对整体比例调节型电动执行机构的重要方面进行了深入的分析与总结：一是组成与原理框图;二是电路器件的作用与电路连接;三是调试的项目与具体方法。     

高性能胎面胶用集成橡胶SBR-IR-SBR

合成出了嵌段聚合物SBR—IR—SBR。通过差热分材(DSC)考察了SBR—IR—SBR生胶的玻璃化转变温度θg，发现生胶分相，两相θg互不影响。DMA分析发现该硫化胶的动态损耗曲线为双峰分布，分别对应总体系的IR相和SBR相。样品652在0℃时的，tgδ值为0．4448，60℃时的tgδ值为0．1012。综合此橡胶的各种常规物性，SBR—IR—SBR是一类高性能胎面胶。     

H∞ filtering for discrete-time systems subject to stochastic missing measurements: a decomposition approach

This paper deals with the problem of H_∞ filtering for discrete-time systems with stochastic missing measurements. A new missing measurement model is developed by decomposing the interval of the missing rate into several segments. The probability of the missing rate in each subsegment is governed by its corresponding random variables. We aim to design a linear full-order filter such that the estimation error converges to zero exponentially in the mean square with a less conservatism while the disturbance rejection attenuation is constrained to a given level by means of an H_∞ performance index. Based on Lyapunov theory, the reliable filter parameters are characterised in terms of the feasibility of a set of linear matrix inequalities. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed design approach.     

Stochastically resilient extended Kalman filtering for discrete-time nonlinear systems with sensor failures

Missing sensor data is a common problem, which severely influences the overall performance of modern data-intensive control and computing applications. In order to address this important issue, a novel resilient extended Kalman filter is proposed for discrete-time nonlinear stochastic systems with sensor failures and random observer gain perturbations. The failure mechanisms of multiple sensors are assumed to be independent of each other with different failure rates. The locally unbiased robust minimum mean square filter is designed for state estimation under these conditions. The performance of the proposed estimation method is verified by means of numerical Monte Carlo simulation of two different nonlinear stochastic systems, involving a sinusoidal system and a Lorenz oscillator system.     

Underactuated fingers controlled by robust and adaptive trajectory following methods

Choosing an appropriate control scheme to alleviate nonlinearities and uncertainties is not a trivial task, especially when models are not easily available and practical evaluation provides the only means for actual performance assessment. Various factors can contribute to these nonlinearities and uncertainties, such as friction and stiction. Thus, this article investigates four different control schemes, namely PID, adaptive, conventional sliding mode control (SMC) and integral sliding mode control (ISMC) which are implemented in the Bristol Elumotion Robot Hand (BERUL) to analyse and overcome the aforementioned problems. The hand has five fingers with 16 joints and all fingers are underactuated. The implementation of the proposed control schemes are challenging since the BERUL fingers have significant friction, stiction and unknown parameters. The fingers are light in weight and fragile. Comparative performance characteristics have shown that the ISMC is the most suitable candidate to provide good experimental trajectory following and positioning control for underactuated BERUL fingers.