网壳结构健康监测中的传感器优化布置

针对网壳结构健康监测提出了一种以损伤可识别性与模态可观测性相协调为目标的传感器优化布置的方法.由于模态数目的选取对基于损伤灵敏度分析的传感器优化布置有很大的影响,因此本文建立了一种同时包含模态独立性信息和损伤灵敏度信息的Fisher信息矩阵,并选取合适的模态数目,然后发展了一种以信息矩阵最大和条件数最小为准则的多目标优化算法.空间网壳数值算例表明,本文提出的传感器优化方法能简单、有效地为空间结构传感器优化布置提供可行方案.     

Some problems associated with the control of distributed structures

Control of structures can be carried out conveniently by modal control, whereby the structure is controlled by controlling its modes. Modal control requires the estimation of the modal states for feedback, which can present a problem. One approach that does not require modal state estimation is direct feedback control, which implies collocated sensors and actuators. This paper examines some problems encountered in direct feedback control of distributed structures in conjunction with pole placement. A perturbation technique permits the computation of control gains for multi-input systems. The paper demonstrates that the difficulties experienced in using direct feedback in conjunction with pole placement are endemic to the approach.This research was sponsored by the Air Force Office of Scientific Research Grant No. AFOSR-83-0017, monitored by Dr. A. K. Amos, whose support is fully appreciated. This paper was presented at the Meeting on Optimal Control and Calculus of Variations, Oberwolfach, West Germany, June 15–21, 1986.     

Nonlinear observer based phase synchronization of chaotic systems

This Letter analyzes the phase synchronization problem of autonomous chaotic systems. Based on the nonlinear state observer algorithm and the pole placement technique, a phase synchronization scheme is designed. The phase synchronization of a new chaotic system is achieved by using this observer controller. Numerical simulations further demonstrate the effectiveness of the proposed phase synchronization scheme.     

基于状态观测器的一类混沌系统的反同步

基于状态观测器方法和极点配置技术，设计出一种反同步方法，使得一类混沌系统达到了反同步.与其他反同步方法相比，所设计的方法更为简便，并且达到反同步的时间短.数值模拟验证了所提方案的有效性. 关键词： 状态观测器 极点配置技术 反同步     

压电桁架作动器/传感器优化配置算法研究

针对自适应压电桁架结构振动控制,建立了作动器/传感器优化配置数学模型,并提出一种优化配置的新方法。为了减少结构分析次数,该方法将近似概念、对偶法和遗传算法相结合,首先采用多点近似技术建立原问题的序列近似问题,再对近似问题中的作动器/传感器位置离散变量和控制增益连续变量采用遗传算法和对偶方法分别寻优的分层优化策略。为了提高近似问题对原问题的逼近程度,本文提出一种适于离散变量结构优化的分段多点近似函数。算例表明本文方法能够以很少的结构分析次数得到最优解。     

次级声源优化布放的局部空间有源降噪

针对区域有源降噪问题,为获得更优降噪效果,根据实际次级通路传递函数,提出次级声源优化布放的有源控制系统并详细比较了两种次级声源优化布放算法与次级声源均匀布放的实际降噪效果。应用的第一种次级声源优化算法是l₂范数约束的约束匹配追踪算法,第二种次级声源优化算法是l₁范数约束的稀疏正则化方法。在全消声室中利用扬声器线阵进行多通道有源降噪实验研究,实验结果表明,在200～1000 Hz,次级声源优化布放的控制系统的平均降噪量比次级声源均匀布放的控制系统的平均降噪量多5 dB左右;在1100～1900 Hz,次级声源优化布放的控制系统的平均降噪量比次级声源均匀布放的控制系统的平均降噪量多11～13 dB左右,次级声源优化布放的控制系统的降噪量分布更加均匀且次级声源输出能量更小。此外,两种优化算法中,稀疏正则化方法的降噪效果更佳。     

Fast, Efficient Equipment Placement Heuristics for Broadband Switched or Internet Router Networks

Planning and designing the next generation of IP router or switched broadband networks seems a daunting challenge considering the many complex, interacting factors affecting the performance and cost of such networks. Generally, this complexity implies that it may not even be clear what constitutes a “good” network design for a particular specification. Different network owners or operators may view the same solution differently, depending on their unique needs and perspectives. Nevertheless, we have observed a core common issue arising in the early stages of network design efforts involving leading-edge broadband switched technologies such as ATM, Frame Relay, and SMDS; or even Internet IP router networks. This core issue can be stated as follows: Given a set of service demands for the various network nodes, where should switching or routing equipment be placed to minimize the Installed First Cost of the network? Note that the specified service demands are usually projections for a future scenario and generally entail significant uncertainty. Despite this uncertainty, we have found that network owners and operators generally feel it is worthwhile to obtain high-level advice on equipment placement with a goal of minimizing Installed First Cost. This paper reports on a heuristic approach we have implemented for this problem that has evolved out of real network design projects. A tool with both a Solution Engine and an intuitive Graphical User Interface has been developed. The approach is highly efficient; for example, the tool can often handle LATA-sized networks in seconds or less on a workstation processor. By using only nodal demands rather than the more complex point-to-point demands usually required in tools of this sort, we have created an approach that is not only highly efficient, but is also a better match to real design projects in which demand data is generally scant and highly uncertain.     

超大规模集成电路布局的优化模型与算法

布局确定集成电路单元在芯片中的具体位置,在单元互不重叠的基础上优化一些性能指标。该问题是NP困难的组合优化问题,是超大规模集成电路物理设计的核心问题之一,对集成电路的性能指标,如线网可布通性、时延、功耗、电路可靠性等有重大影响。在现代的集成电路设计中,布局问题通常包含数百万个集成电路单元,以及大小相异的异质性模块,和各种复杂的布局约束。目前的超大规模集成电路布局算法通常分解为总体布局、布局合法化和详细布局三个步骤。根据近年来集成电路布局算法的研究进展,综述并分析集成电路的总体布局、布局合法化和详细布局的相关优化模型和算法,并展望进一步的研究方向。     

Training Data Selection and Optimal Sensor Placement for Deep-Learning-Based Sparse Inertial Sensor Human Posture Reconstruction

Although commercial motion-capture systems have been widely used in various applications, the complex setup limits their application scenarios for ordinary consumers. To overcome the drawbacks of wearability, human posture reconstruction based on a few wearable sensors have been actively studied in recent years. In this paper, we propose a deep-learning-based sparse inertial sensor human posture reconstruction method. This method uses bidirectional recurrent neural network (Bi-RNN) to build an a priori model from a large motion dataset to build human motion, thereby the low-dimensional motion measurements are mapped to whole-body posture. To improve the motion reconstruction performance for specific application scenarios, two fundamental problems in the model construction are investigated: training data selection and sparse sensor placement. The problem of deep-learning training data selection is to select independent and identically distributed (IID) data for a certain scenario from the accumulated imbalanced motion dataset with sufficient information. We formulate the data selection into an optimization problem to obtain continuous and IID data segments, which comply with a small reference dataset collected from the target scenario. A two-step heuristic algorithm is proposed to solve the data selection problem. On the other hand, the optimal sensor placement problem is studied to exploit most information from partial observation of human movement. A method for evaluating the motion information amount of any group of wearable inertial sensors based on mutual information is proposed, and a greedy searching method is adopted to obtain the approximate optimal sensor placement of a given sensor number, so that the maximum motion information and minimum redundancy is achieved. Finally, the human posture reconstruction performance is evaluated with different training data and sensor placement selection methods, and experimental results show that the proposed method takes advantages in both posture reconstruction accuracy and model training time. In the 6 sensors configuration, the posture reconstruction errors of our model for walking, running, and playing basketball are 7.25°, 8.84°, and 14.13°, respectively.     

Optimizing source and receiver placement in multistatic sonar networks to monitor fixed targets

Multistatic sonar networks consisting of non-collocated sources and receivers are a promising development in sonar systems, but they present distinct mathematical challenges compared to the monostatic case in which each source is collocated with a receiver. This paper is the first to consider the optimal placement of both sources and receivers to monitor a given set of target locations. Prior publications have only considered optimal placement of one type of sensor, given a fixed placement of the other type. We first develop two integer linear programs capable of optimally placing both sources and receivers within a discrete set of locations. Although these models are capable of placing both sources and receivers to any degree of optimality desired by the user, their computation times may be unacceptably long for some applications. To address this issue, we then develop a two-step heuristic process, Adapt-LOC, that quickly selects positions for both sources and receivers, but with no guarantee of optimality. Based on this, we also create an iterative approach, Iter-LOC, which leads to a locally optimal placement of both sources and receivers, at the cost of larger computation times relative to Adapt-LOC. Finally, we perform computational experiments demonstrating that the newly developed algorithms constitute a powerful portfolio of tools, enabling the user to slect an appropriate level of solution quality, given the available time to perform computations. Our experiments include three real-world case studies.