一种复合型数值方法的改进与算法实现

文中对原有的复合方法进行了改进,提出了一种新的复合型数值方法,这种方法解决了原方法求解含源项的问题时存在数值震荡的缺点。为了验证算法的有效性,对计算流体力学中一阶浅水波问题的两个典型的算例进行了数值模拟,在解的光滑性、锐利性等几个方面做了分析,结果表明改进后的方法既消除了数值震荡现象,又能准确地逼近真解,求出锐利的间断,是一种行之有效的数值方法。     

Frequency domain solution to delay-type Nehari problem

This paper generalizes the frequency-domain results on the delay-type Nehari problem in the stable case to the unstable case. The solvability condition of the delay-type Nehari problem is formulated in terms of the nonsingularity of three matrices. The optimal value γ_opt is the maximal γ∈(0,∞) such that one of the three matrices becomes singular. All sub-optimal compensators are parameterized in a transparent structure incorporating a modified Smith predictor.     

立式旋风锅炉的燃烧自适应控制

分析了立式旋风锅炉的燃烧特点和燃烧系统动态特性，讨论了它的软硬件构成及其功能。     

积分分离PID算法的电阻炉温度控制系统

为使大惯性、纯滞后的电阻炉温度控制系统的动态性能和稳态精度满足要求,提出了Smith预估结合积分分离PID算法;设计了温度控制器的硬件系统;对控制系统进行辨识;分析了Smith预估结合积分分离PID算法与单纯Smith预估控制算法的区别,并对两种控制算法进行了比较分析,确定了电阻炉温度控制系统参数;最后对Smith预估结合积分分离PID算法进行了电阻炉的温度控制实验;实验结果表明,采用Smith预估结合积分分离PID算法提高了电阻炉温度控制系统的稳定性,降低了系统的超调,稳态精度达到0.2℃,其动态性能和稳态精度满足系统控制要求.     

气动人工肌肉手臂的神经网络Smith预估控制

针对含时滞d的1关节气动人工肌肉(PAM)手臂,用三层递归神经网络(RNN),建立PAM手臂包含时滞的模型(即非线性Smith预估器),并超前d步预测PAM手臂的输出角度.将此超前d步的预测值作为反馈量,与设定值相比较得到的误差作为PID控制器输入量,实现Smith预估PID控制.同时每一步都用RNN模型当前时刻的输出值与PAM手臂当前时刻实际输出值之差的平方做为RNN权值的在线调整准则对RNN预测模型的权值进行在线调整,以自适应PAM手臂的不确定性和时变性.使用Matlab通过串口和研华亚当模块对实物PAM手臂进行控制,控制效果表明所提出的Smith预估PID控制算法比常规PID控制算法的性能有显著提高,证明所提出的算法是有效的和切实可行的.     

Generalized multi-scale control scheme for cascade processes with time-delays

The cascade control is a well-known technique in process industry to improve regulatory control performance. The use of the conventional PI/PID controllers has often been found to be ineffective for cascade processes with long time-delays. Recent literature report has shown that the multi-scale control (MSC) scheme is capable of providing improved performance over the conventional PID controllers for processes characterized by long time-delays as well as slow RHP zeros. This paper presents an extension of this basic MSC scheme to cascade processes with long time-delays. This new cascade MSC scheme is applicable to self-regulating, integrating and unstable processes. Extensive numerical studies demonstrate the effectiveness of the cascade MSC scheme compared with some well-established cascade control strategies.     

Boosting performance of transactional memory through O-GEHL predictors

Time-based Software Transactional Memory (STM) exploits a global clock to validate transactional data and guarantee consistency of transactions. While this method is simple to implement it results in contentions over the clock if transactions commit simultaneously. The alternative method is thread local clock (TLC) which exploits local variables to maintain consistency of transactions. However, TLC may increase false aborts and degrade performance of STMs. In this paper, we analyze global clock and TLC in the context of STM systems, highlighting both the implementation trade-offs and the performance implications of the two techniques. We demonstrate that neither global clock nor TLC is optimum across applications. To counter this challenge, we introduce two optimization techniques: The first optimization technique is Adaptive Clock (AC) which dynamically selects one of the two validation techniques based on probability of conflicts. AC is a speculative approach and relies on software O-GEHL predictors to speculate future conflicts. The second optimization technique is AC+ which reduces timing overhead of O-GEHL predictors by implementing the predictors in hardware. In addition, we exploit information theory to eliminate unnecessary computational resources and reduce storage requirements of the O-GEHL predictors. Our evaluation with TL2 and Stamp benchmark suite reveals that AC is effective and improves execution time of transactional applications up to 65%.     

采用Smith预估器模型的时滞系统自适应控制

在实际生产控制系统中时滞现象相当普遍,而传统的PID控制方法对时滞系统的控制很难达到满意的效果且易引起系统的不稳定.Smith预估器是一种广泛应用于时滞系统闭环控制的有效方法,但存在预估器模型和被控对象参数不匹配时系统控制特性的劣化甚至发生振荡发散的问题.本文提出了一种基于李雅普诺夫稳定性理论,用于改善Smith预估器参数失配时控制特性的模型参考自适应控制方法,阐述了其基本原理并推导了1阶系统的自适应律,然后通过数值仿真计算进行了验证.理论分析推导和仿真计算结果表明,Smith预估器和自适应控制方法的结合明显改善了对时滞系统的控制性能,防止了系统的不稳定性,因而在一定程度上解决了Smith预估器存在的上述问题,取得了较好的效果,有望在实际的时滞系统和设备的过程控制中得到广泛的应用.     

A Novel Probabilistic Saturating Counter Design for Secure Branch Predictor

In a modern processor,branch prediction is crucial in effectively exploiting the instruction-level parallelism for high-performance execution.However,recently exposed vulnerabilities reveal the urgency to improve the security of branch predictors.The vital cause of the branch predictor vulnerabilities is that the update strategy of the saturating counter is deterministic.As a fundamental building block in a modern branch predictor,previous studies have paid too much attention to the performance and hardware cost and ignored the security of saturating counter.This leaves attackers with the opportunities to perform side-channel attacks on the branch predictor.This paper focuses on the saturating counter to explore a secure and lightweight design to mitigate branch predictor side-channel attacks.Instead of applying the isolation mechanism to branch predictor resources,we propose a novel probabilistic saturating counter design to confuse the attacker's perception of the victim's behaviour.It changes the conventional deterministic state transition function to a probabilistic state transition function.When a branch is committed,the conventional saturating counter needs to be updated about whether the prediction results are correct or not.While for the probabilistic saturating counter,the branch predictor determines whether the update is performed based on the update probability.The probabilistic saturating counter dramatically reduces the ability of the attacker to spy the saturating counter's state.Our analyses using a cycle-accurate simulator suggest that the proposed mechanism incurs 2.4％ performance overhead and hardware cost while providing strong protection.     

生鲜食品微生物预测及评估平台研究

针对如何快速、有效地评估食品的安全,预测出食品的货架期,拟建立一个生鲜食品微生物预测与品质评估管理平台,通过对生鲜食品中微生物菌群基本状况及优势菌群在生长规律的数据采集,分别构建不同的温度下优势菌群的一级和二级生长模型,实现对生鲜食品货架期的预测。阐述了该平台的基本组成,工作流程,主要数据结构和主要数学模型。该平台能帮助预测生鲜食品在运输、储存和加工过程中的货架期并进行环境控制。