切换系统的鲁棒二次公共Lyapunov函数矩阵寻找算法

为了获得不确定线性切换系统稳定性判别的公共二次Lyapunov函数寻找方法,提出了鲁棒公共二次Lyapunov函数的概念,运用矩阵不等式分析,得到了在鲁棒稳定矩阵集对合和不对合的情况下,鲁棒公共二次Lyapunov函数存在的充分性条件以及LMI形式的递推搜寻算法。获得的结果便于计算机实现,对不确定切换系统鲁棒稳定性判别具有一定价值。应用仿真测试验证了其正确性。     

基于观测器的不确定T-S模糊系统鲁棒镇定

为带有参数不确定性的T-S模糊控制系统提出了新的基于观测器的鲁棒输出镇定条件. 该条件用来设计模糊控制器和模糊观测器. 为了设计模糊控制器和模糊观测器, 用T-S模糊模型来表示非线性系统, 并运用平行分布补偿观念. 充分条件基于二次Lyapunov函数, 通过将模糊系统的鲁棒镇定条件表述为一系列矩阵不等式, 比以往文献中列出的条件具有更小的保守性. 该不等式为双线性矩阵不等式, 可分两步骤先后解得使T-S模糊系统镇定的控制器增益和观测器增益. 最后, 通过对一个具有不确定性的连续时间非线性系统控制的例子证明了提出方法比以往方法更宽松.     

广义相似不确定组合系统的二次鲁棒分散镇定

描述了两个线性控制系统间的广义相似性,并研究了具有广义相似结构的组合系统二次鲁棒分散镇定问题,给出了可二次鲁棒分散镇定的一个充分条件及控制器,研究表明,若系统具有相似结构,则其控制器的设计将大为简化,仿真实例说明了所采用方法的有效性。     

基于模糊Lyapunov函数的离散模糊时滞系统H∞控制

研究一类离散Takagi-Sugeno（T-S）模糊时滞系统的稳定性分析和H∞控制器设计问题.通过构造适当的模糊Lyapunov函数,给出一种新型的基于线性矩阵不等式（LMI）的时滞相关稳定性充分条件,该条件比以往结果具有更小的保守性;在此基础上,提出了H∞模糊状态反馈控制器的设计方法.仿真结果表明了所提方法的有效性.     

一类不确定多输入模糊双线性系统的鲁棒H∞控制

针对一类带有参数不确定性和干扰的多输入模糊双线性系统(FBS)的鲁棒H_∞控制问题,使用并行分布补偿算法(PDC)设计了模糊控制器,得到了整个模糊控制系统鲁棒全局稳定的充分条件,控制器的设计可以通过求解一系列线性矩阵不等式(LMI)获得.仿真例子验证了方法的有效性.     

一类不确定切换模糊组合系统的分散鲁棒镇定

提出一种切换模糊组合系统模型并讨论其鲁棒控制问题.分别利用单Lyapunov函数方法和多Lyapunov函数方法设计出分散切换律和控制器,给出了系统在分散切换律和分散控制器作用下的矩阵不等式可镇定条件.仿真结果表明了该设计方法的有效性.     

一类不确定离散切换模糊时滞系统的鲁棒非脆弱控制

针对一类不确定离散切换模糊时滞系统,研究了在控制器增益存在摄动情况下的稳定性问题.利用切换技术和多Lyapunov函数方法,并以矩阵不等式形式给出了非脆弱状态反馈控制器存在的充分条件和切换律设计.最后通过数值仿真算例验证了设计方法的有效性和可行性.     

不确定时滞系统无记忆鲁棒镇定控制

本文研究了一类状态和控制同时存在滞后的线性时变不确定时滞系统的鲁棒镇定控制问题，针对所有容许的时变未知且有界的不确定性，得到了确保闭环系统二次稳定的充分条件。文中进一步把不确定时滞系统的二次镇定控制器设计问题等价为线性时不变系统的状态反馈标准Ｈ∞控制问题，并由此得到鲁棒镇定控制器综合设计方法。     

不确定离散广义时滞系统的鲁棒非脆弱H∞控制

针对一类参数不确定离散时滞广义系统,研究其鲁棒非脆弱H∞状态反馈控制器的设计问题.系统中的不确定项参数与控制器的增益变化同时具有线性分式形式的范数有界.首先,利用Lyapunov函数理论,研究该标称系统的鲁棒H∞控制问题;其次,以线性矩阵不等式(LMI)形式给出该系统的鲁棒非脆弱H∞控制器存在的充分条件及设计方法.该控...     

基于自适应事件触发的时滞系统分布式${l_2}text{-}{l_infty}$滤波

研究一类基于自适应事件触发机制的时滞系统分布式滤波问题.自适应事件触发条件由滤波器自身最新释放数据、当前时刻估计值及邻居节点最新释放数据共同决定.此事件触发机制采用阈值自适应调节方案,阈值参数在保证滤波器性能的前提下根据滤波误差动态变化,最大程度上节约网络通信资源.首先,给出滤波误差系统均方指数稳定的充分条件;其次,构造一个Lyapunov函数来分析滤波误差系统满足l2-l∞的性能指标;再次,设计离散时滞系统分布式l₂-l_∞滤波器,并通过线性矩阵不等式方法求解滤波器参数;最后,通过仿真实例说明滤波器能够降低系统时滞带来的影响,且在保证滤波性能前提下减少通信次数,节约网络资源.     

Tuples of Disjoint $\mathsf{NP}$ -Sets

Disjoint -pairs are a well studied complexity-theoretic concept with important applications in cryptography and propositional proof complexity. In this paper we introduce a natural generalization of the notion of disjoint -pairs to disjoint k-tuples of -sets for k≥2. We define subclasses of the class of all disjoint k-tuples of -sets. These subclasses are associated with a propositional proof system and possess complete tuples which are defined from the proof system. In our main result we show that complete disjoint -pairs exist if and only if complete disjoint k-tuples of -sets exist for all k≥2. Further, this is equivalent to the existence of a propositional proof system in which the disjointness of all k-tuples is shortly provable. We also show that a strengthening of this conditions characterizes the existence of optimal proof systems. An extended abstract of this paper appeared in the proceedings of the conference CSR 2006 (Lecture Notes in Computer Science 3967, 80–91, 2006). Supported by DFG grant KO 1053/5-1.     

Design and Validation of an ${\mathcal{L}}_{1}$ Adaptive Controller for Mini-UAV Autopilot

The dynamics of Unmanned Aerial Vehicles (UAVs) is nonlinear and subject to external disturbances. The scope of this paper is the test of an \({\mathcal{L}_1}\) adaptive controller as autopilot inner loop controller candidate. The selected controller is based on piecewise constant adaptive laws and is applied to a mini-UAV. Navigation outer loop parameters are regulated via PID control. The main contribution of this paper is to demonstrate that the proposed control design can stabilize the nonlinear system, even if the controller parameters are selected starting from a decoupled linear model. The main advantages of this technique are: (1) the controller can be implemented for both linear and nonlinear systems without parameter adjustment or tuning procedure, (2) the controller is robust to unmodeled dynamics and parametric model uncertainties. The design scheme of a customized autopilot is illustrated and different configurations (in terms of mass, inertia and airspeed variations) are analyzed to validate the presented approach.     

An $\mathsf{EDF}$ -based restricted-migration scheduling algorithm for multiprocessor soft real-time systems

There has been much recent interest in the use of the earliest-deadline-first ( ) algorithm for scheduling soft real-time sporadic task systems on identical multiprocessors. In hard real-time systems, a significant disparity exists between -based schemes and Pfair scheduling: on M processors, the worst-case schedulable utilization for all known variants is approximately M/2, whereas it is M for optimal Pfair algorithms. This is unfortunate because -based algorithms entail lower scheduling and task-migration overheads. However, such a disparity in schedulability can be alleviated by easing the requirement that all deadlines be met, which may be sufficient for soft real-time systems. In particular, in recent work, we have shown that if task migrations are not restricted, then (i.e. , global ) can ensure bounded tardiness for a sporadic task system with no restrictions on total utilization. Unrestricted task migrations in global may be unappealing for some systems, but if migrations are forbidden entirely, then bounded tardiness cannot be guaranteed. In this paper, we address the issue of striking a balance between task migrations and system utilization by proposing an algorithm called , which is based upon and treads a middle path, by restricting, but not eliminating, task migrations. Specifically, under , the ability to migrate is required for at most M−1 tasks, and it is sufficient that every such task migrate between two processors and at job boundaries only. , like global , can ensure bounded tardiness to a sporadic task system as long as the available processing capacity is not exceeded, but, unlike global , may require that per-task utilizations be capped. The required cap is quite liberal, hence, should enable a wide range of soft real-time applications to be scheduled with no constraints on total utilization.

融合稀疏自表示和残差驱动的自适应模糊C均值聚类

提出一种融合稀疏自表示和残差驱动的自适应模糊C均值聚类算法(R²AFCM).该算法的优点主要体现在以下两个方面:1)利用稀疏自表示技术求解样本数据的字典矩阵,并将其表征的全局信息考虑到目标函数中,充分考虑数据分布特点,改进传统模糊C均值聚类算法重点关注局部信息的不足; 2)在目标函数中引入加权残差估计正则化项,与自适应模糊聚类算法的正则化项相结合,约束模型训练,有效降低混合噪声对分割结果的影响.在磁共振成像、VOC 2012数据集以及自然图像上进行对比实验,结果表明,所提出的聚类算法在添加了20%椒盐噪声和均值为0.4、方差为0.01的高斯噪声,以及50%椒盐噪声和均值为0、方差为0.1的混合噪声下与其他算法相比,具有更高的分割精度和更强的鲁棒性.