离散不确定系统预估+ 步长修正变结构控制

在现有文献的基础上，给出一种预估＋步长修正的离散变结构控制律设计方法，该方法可用于离散时间不确定系统变结构控制，有效地抑制切换函数的发散振荡，克服现有方法中条件限制过程的缺点，仿真结果表明，该方法具有收敛性好，抖振小，鲁棒性强的优点。     

一类不确定离散时间系统的鲁棒故障诊断滤波器优化设计方法

研究线性不确定离散时间系统的鲁棒故障诊断滤波器设计问题。基于新提出的性能指标函数，将不确定离散时间系统的故障诊断漶波器设计问题归结为肌优化问题，并通过选择适当的后滤波器和观测器增益矩阵，得到未知输入和模型不确定性鲁棒性的最优解。     

An LMI approach to design robust fault detection filter for uncertain LTI systems

In this paper, the robust fault detection filter design problem for uncertain linear time-invariant (LTI) systems with both unknown inputs and modelling errors is studied. The basic idea of our study is to use an optimal residual generator (assuming no modelling errors) as the reference residual model of the robust fault detection filter design for uncertain LTI systems with modelling errors and, based on it, to formulate the robust fault detection filter design as an H_∞ model-matching problem. By using some recent results of H_∞ optimization, a solution of the optimization problem is then presented via a linear matrix inequality (LMI) formulation. The main results include the development of an optimal reference residual model, the formulation of robust fault detection filter design problem, the derivation of a sufficient condition for the existence of a robust fault detection filter and a construction of it based on the LMI solution parameters, the determination of adaptive threshold for fault detection. An illustrative design example is employed to demonstrate the effectiveness of the proposed approach.     

一种新颖的图像水印嵌入方法

An novel embedding method for image watermark based on wavelet transform is proposed. With this method ,the value of each pels is modified directly,so that a bit of watermark information is embedded in every pel-s. Before emeded,the original image is decomposed by wavelet transform,and then,a correlation mask for every imagepels is confirmed by the characteristic and tree structure ralation of the wavelet coefficients. At last, the modified val-ue of every pels is controlled by its corresponding mask for watermark information embedded. The experimental re-sults show that the embedded digital watermarks with this proposed method are invisible and robust enough againstthe commonly used image processing techniques.     

过热器蒸汽温度状态观测器的鲁棒性分析

工程中过热蒸汽温度作为被控对象通常是n阶大惯性环节，且状态不可测。以常规手段，通常很难达到理想的控制效果。该文以这个实际工程问题为研究背景，根据状态观测器和鲁棒观测器设计的理论，研究过热器蒸汽温度动态特性状态重构的实用技术，分析采用高阶惯性环节作为过热器的状态观测器的适用性。得出在保持系统稳定的前提下，惰性区时间常数的允许变化范围。通过分析得知状态观测器确定时，此范围只和状态反馈增益阵有关。仿真试验验证了理论分析结果的正确性。     

参数不确定系统的H∞估计问题的显式解和中心解

研究在连续时间情形下的具有部分参数不确定性的系统的H∞状态估计问题,它可 以被化简为带有一个自由可调参数对象的H∞状态估计,由此可得到滤波器的简洁通解显 式.并进一步研究了H∞估计的中心解,以及它与卡尔曼滤波器的关系.实例计算表明,对于 参数具有不确定性的系统,H∞滤波器的性能明显地优于卡尔曼滤波器.     

鲁棒稳定控制器设计

提出了一种新的鲁棒稳定控制器设计方法。利用它能够成功地解决当控对角具有极点穿越虚轴时，鲁棒器的设计问题。     

Discrete Adaptive Sliding Mode Control of a State-Space System with a Bounded Disturbance

This paper presents the discrete adaptive sliding mode control of a state-space system in the presence of a bounded disturbance. The delta form of the discrete state-space model is used as it closely resembles that of the continuous model. The control law takes into account of the effect of the disturbance by using its approximate value. The system behavior in the vicinity of the sliding surface is studied. It is shown that the adaptive controller leads to a stable closed-loop system. Also, simulation results are presented to illustrate the features of the proposed adaptive control strategy.     

Worst-case properties of the uniform distribution and randomized algorithms for robustness analysis

In this paper we study aprobabilistic approach which is an alternative to the classical worst-case algorithms for robustness analysis and design of uncertain control systems. That is, we aim to estimate the probability that a control system with uncertain parametersq restricted to a boxQ attains a given level of performance γ. Since this probability depends on the underlying distribution, we address the following question: What is a “reasonable” distribution so that the estimated probability makes sense? To answer this question, we define two worstcase criteria and prove that the uniform distribution is optimal in both cases. In the second part of the paper we turn our attention to a subsequent problem. That is, we estimate the sizes of both the so-called “good” and “bad” sets via sampling. Roughly speaking, the good set contains the parametersq∈Q with a performance level better than or equal to γ while the bad set is the set of parametersq∈Q with a performance level worse than γ. We give bounds on the minimum sample size to attain a good estimate of these sets in a certain probabilistic sense.     

基于改进的BP网络误差修正的广义预测控制

该文利用预测误差的历史数据，基于改进的BP神经网络，对系统的建模误差进行预测。该网络采用了修正激励函数的BP算法，预测性能好，能够克服标准BP算法中Sigmoid函数的不足，加快了网络的学习速度。并将其与模型预测相结合构成广义预测控制算法，有效地克服了模型失配的影响，提高了控制的速度，同时引入控制增量增益，利用这个自由度来提高闭环的稳定鲁棒性。仿真结果表明了该算法的有效性。