Gait recognition using active shape model and motion prediction

This study presents a novel, robust gait recognition algorithm for human identification from a sequence of segmented noisy silhouettes in a low-resolution video. The proposed recognition algorithm enables automatic human recognition from model-based gait cycle extraction based on the prediction-based hierarchical active shape model (ASM). The proposed algorithm overcomes drawbacks of existing works by extracting a set of relative model parameters instead of directly analysing the gait pattern. The feature extraction function in the proposed algorithm consists of motion detection, object region detection and ASM, which alleviate problems in the baseline algorithm such as background generation, shadow removal and higher recognition rate. Performance of the proposed algorithm has been evaluated by using the HumanID Gait Challenge data set, which is the largest gait benchmarking data set with 122 objects with different realistic parameters including viewpoint, shoe, surface, carrying condition and time.     

二阶系统非一致目标跟踪混合自适应迭代学习控制

针对一类含有时变和时不变参数的二阶非线性系统,利用Backstepping方法,提出了一种新的自适应迭代学习控制方法,该方法由微分-差分型自适应律和学习控制律组成,保证对非一致目标的跟踪误差的平方在一个有限区间上的积分收敛于零,克服了传统的迭代学习控制对目标轨线的限制,可以跟踪非一致目标轨线。通过构造复合能量函数,给出了闭环系统收敛的一个充分条件。仿真结果说明了该方法的可行性和有效性。     

Reduced basis method for managed pressure drilling based on a model with local nonlinearities

To circumvent restrictions of conventional drilling methods, such as slow control actions and inability to drill depleted reservoirs, a drilling method called managed pressure drilling (MPD) has been developed. In MPD, single-phase flow processes can be modeled as a feedback interconnection of a high-order linear system and a low-order nonlinear system. These nonlinearities appear locally both inside and at the boundaries of the computational domain. To obtain a fast simulation platform for real-time purposes (eg, online model-based controller implementation), model order reduction is required for MPD. However, the local nonlinearities render applying model order reduction techniques challenging. In this study, a new approach is proposed to deal with such nonlinearities within the reduced basis (RB) context and it is successfully tested on a model for MPD. Contrary to the classical RB technique, the proposed approach not only does not generate nonphysical spikes at the locations of these local nonlinearities but also yields high speedup factors. The obtained reduced-order model can be used for efficient online simulation and controller design for drilling systems with MPD.     

基于加权Lucas-Kanade算法的目标跟踪

针对传统的序列图像目标跟踪方法难以适应复杂背景干扰、目标形状变化以及目标位置非规则抖动的问题,提出了一种基于加权Lucas-Kanade算法的目标跟踪新方法.首先引入搜索模板,估计出目标在实时图像中的位置并将其作为加权Lucas-Kanade算法的迭代初始值,然后计算权值函数,利用当前模板和初始模板进行两次跟踪,得到目...     

A neural network model for on-line control of flexible manufacturing systems

This research investigates the potential of using a neural network approach in real-time control of flexible manufacturing systems. A hierarchical manufacturing controller, consisting of two neural network structures, is proposed. The first neural system participates in the feasibility analysis, and the other, at the lower level, in the process of dispatching and control. At the first level, a Sigma-Pi type of connection is used to translate work-in-process (WIP) move requests into directed arcs. Through a filter scheme, infeasible arcs are identified and eliminated from further consideration. At the second level, a modified Hopfield-Tank model is developed to determine the correct moves. Its goal is to deliver the right WIP to the right workstation, and process it at the right time. An example is used throughout the paper to illustrate the architecture developed. This two-phase control procedure provides adaptability, speed, and good solution quality which are important for real-time control of flexible manufacturing systems.     

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)—the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets.     

An inverse approach in obtaining shape functions for a superconvergent thin plate element

This article presents an inverse approach to provide shape functions associate with a superconvergent thin plate element formulation. In the proposed approach, candidates for shape functions of an element are selected using a series of functions such as, trigonometric series, simple and hierarchical polynomials or a combination of them. Next, one imposes all the physical, geometrical, compatibility and completeness constraints associated with the concerned element on these function. In the final stage, the unknown parameters of the shape functions are determined by minimizing the discrimination errors in the element formulation. The proposed method is employed to determine the shape functions associate with the superconvergent plate element formulation. The accuracy of the obtained formulation is examined against previously developed plate models using several numerical examples. These comparisons indicate the developed model provides more accurate results both in local and global coordinates system.     

LMI-based robust voltage tracking control for a class of renewable energy systems

This paper introduces a method of robust voltage tracking control for a class of renewable energy systems, which uses a linear matrix inequality (LMI)-based approach. A remodeling method is introduced where the nonlinear model of the renewable energy system is represented as a nonlinear combination of linear subsystems with state-dependent parameters (the so-called linear state-dependent parameter system model, LSDPM). Next, the remodeling method is applied to a boost converter, a photovoltaic (PV) system, and a wind energy conversion system as examples. A robust output voltage tracking approach is proposed based on the LSDPM. Using Lyapunov’s direct method, controller stability analyses are expressed as LMI formulations. Powerful numerical toolboxes then solve for the controller gains. The advantages of this approach include: i) the generalized remodeling technique is applicable to a wide variety of renewable energy systems; ii) it creates a unified LMI-based design framework for multiple control objectives; iii) it provides numerically solved control gains; and iv) it provides robust tracking control for the multiple objectives of renewable energy systems. Using an LMI-based robust voltage tracking controller is an accurate and effective method of control for many types of renewable energy systems. Finally, practical DSP-based experiments are carried out using the buck converter as an example. The satisfactory results of these experiments verify the theoretical derivations for this control method.     

OFDM水声通信系统动态OMP信道跟踪算法

针对正交频分复用(Orthogonal Frequency Division Multiplexing, OFDM)水声通信系统中最小二乘(Least Square,LS)信道估计算法和静态压缩感知信道估计算法分别存在估计精度低、导频开销大和计算复杂度高、实时性差的缺点,利用水声信道冲激响应的时域相关性,通过建立动态稀疏观测模型,提出一种动态正交匹配追踪(Dynamic Orthogonal MatchingPursuit,D-OMP)信道跟踪算法。该算法仅在初始时刻进行一次完整的正交匹配追踪(OrthogonalMatching Pursuit, OMP)信道估计获取信道支撑集,之后通过连续跟踪前一时刻信道支撑集的变化来跟踪信道。仿真结果表明,在导频开销相同的情况下,与传统LS算法、经典OMP算法相比,所提算法具有更好的信道跟踪性能和较低的算法复杂度。     

光电成像跟踪系统的实时数据融合技术研究

光电成像跟踪系统需要保证不同目标的自适应识别,同时严格按照时间序列执行的图像处理又是一个强实时性过程。实时融合跟踪技术提出并行执行多个算法组以适应不同类型目标的识别,并通过像素级、特征级和决策级的同时融合处理保证了系统跟踪的稳定性,最后在嵌入式并行处理硬件平台上有效解决了对运动目标的自适应跟踪。文中详细阐述了实时融合跟踪技术的技术思想和技术路线,在剖析其并行结构的基础上完成了光电成像跟踪系统的嵌入式硬件并行平台的设计和实现,取得了显著的工程应用成果。     

Automatic target tracking in FLIR image sequences using intensity variation function and template modeling

A novel automatic target tracking (ATT) algorithm for tracking targets in forward-looking infrared (FLIR) image sequences is proposed in this paper. The proposed algorithm efficiently utilizes the target intensity feature, surrounding background, and shape information for tracking purposes. This algorithm involves the selection of a suitable subframe and a target window based on the intensity and shape of the known reference target. The subframe size is determined from the region of interest and is constrained by target size, target motion, and camera movement. Then, an intensity variation function (IVF) is developed to model the target intensity profile. The IVF model generates the maximum peak value where the reference target intensity variation is similar to the candidate target intensity variation. In the proposed algorithm, a control module has been incorporated to evaluate IVF results and to detect a false alarm (missed target). Upon detecting a false alarm, the controller triggers another algorithm, called template model (TM), which is based on the shape knowledge of the reference target. By evaluating the outputs from the IVF and TM techniques, the tracker determines the real coordinates of one or more targets. The proposed technique also alleviates the detrimental effects of camera motion, by appropriately adjusting the subframe size. Experimental results using real-life long-wave and medium-wave infrared image sequences are shown to validate the robustness of the proposed technique.     

基于被动式传感器的目标跟踪算法研究

仅有角度量测的被动式单传感器跟踪搜索系统有广泛的应用前景,但现有的针对性跟踪算法并不能很好的处理实际问题,失跟现象常常发生。本文对现有算法所存在的问题进行了深入研究,并提出了相应的改进算法。通过对机动目标运动分析,总结出角度向量在时间域中的变化规律,通过引入新的计算向量,对原算法残差计算进行了修正。它对基于单个被动传感器的纯方位跟踪问题的处理提供了新的思路。仿真实验及实际应用已证明了该算法有效性。     

A Framework for Reliability Prediction During Product Development Process Incorporating Engineering Judgments

This paper presents a comprehensive framework for reliability prediction during the product development process. Early in the product development process, there is typically little or no quantitative evidence to predict the reliability of the new concept except indirect or qualitative information. The proposed framework addresses the issue of utilizing qualitative information in the reliability analysis. The framework is based on the Bayesian approach. The fuzzy logic theory is used to enhance the capability of the Bayesian approach to deal with qualitative information. This paper proposes to extract the information from various design tools and design review records and incorporate it into the Bayesian framework through a fuzzy inference system. The Weibull distribution is considered as failure/survival time distribution with the assumption of a known value of shape factor. Initial parameters of the Weibull distribution are estimated from warranty data of prior systems to estimate the initial Bayesian parameter ( λ_t). The applicability of the framework is illustrated via an example.     

基于工业焊接小车的视觉伺服控制算法研究

针对基于视觉传感器的焊接小车，提出了提高跟踪精度和鲁棒性的视觉伺服控制方法。首先，建立了图像特征的数学模型，并设计了错误数据的检测算法，其次，对于折线焊缝跟踪过程中存在的位置延迟问题，采用了一种自适应视觉伺服控制结构。这种自适应结构在线检测焊缝方向，并能够在焊缝方向发生变化时对控制参数进行相应的调整。针对该控制结构，设计了基于Kalman滤波器的焊缝方向变化检测算法、参考像素坐标调整算法以及预测与实时调整相结合的控制方法。焊缝自动跟踪实验表明所提方法具有较强的鲁棒性和较高的精度。     

HVAC系统的模糊预测函数控制器设计

针对暖通空调HVAC系统中由于存在高度非线性、时变特征以及扰动和不确定性等因素而难以控制的特点，提出基于Takagi-Sugeno(T-S)模糊模型的预测函数控制器设计方法。该方法通过最小二乘辨识算法建立系统的模糊T-S模型，然后基于模糊全局线性化预测模型，采用预测函数控制算法设计系统控制律。仿真实验结果表明该算法是一种跟踪性能好、鲁棒性强的有效控制方法。与常规的PID控制器相比，该方法具有超调量小、调整时间短等优良的动态性能。     

An efficient memetic algorithm for 3D shape matching problems

Shape representation plays a vital role in any shape optimization exercise. The ability to identify a shape with good functional properties is dependent on the underlying shape representation scheme, the morphing mechanism and the efficiency of the optimization algorithm. This article presents a novel and efficient methodology for morphing 3D shapes via smart repair of control points. The repaired sequence of control points are subsequently used to define the 3D object using a B-spline surface representation. The control points are evolved within the framework of a memetic algorithm for greater efficiency. While the authors have already proposed an approach for 2D shape matching, this article extends it further to deal with 3D shape matching problems. Three 3D examples and a real customized 3D earplug design have been used as examples to illustrate the performance of the proposed approach and the effectiveness of the repair scheme. Complete details of the problems are presented for future work in this direction.     

A novel Kalman filter for frequency estimation of distorted signalsin power systems

A simple and novel approach in the design of an extended Kalman filter (EKF) for the measurement of power system frequency has been presented in this paper. The design principles and the validity of the model have been outlined. The performance of this filter has been compared with some of the existing methods for estimating the frequency of a signal under noisy conditions. The feasibility of the proposed filter has been tested in the laboratory under worst-case measurement and network conditions, which might occur in a typical power system. Also, the proof of the stability for the proposed filter has been discussed for a single sinusoid. It has been found that the proposed algorithm is suitable for real-time applications especially when the frequency changes are abrupt and the signal is corrupted with noise and other disturbances due to harmonics     

基于序贯层次Kriging模型的微型飞行器机身结构设计优化

在基于仿真模型的工程设计优化中,采用高精度、高成本的分析模型会导致计算量大,采用低精度、低成本的分析模型会导致设计优化结果的可信度低,难以满足实际工程的要求。为了有效平衡高精度与低成本之间的矛盾关系,通过建立序贯层次Kriging模型融合高/低精度数据,采用大量低成本、低精度的样本点反映高精度分析模型的变化趋势,并采用少量高成本、高精度的样本点对低精度分析模型进行校正,以实现对优化目标的高精度预测。为了避免层次Kriging模型误差对优化结果的影响,将层次Kriging模型与遗传算法相结合,根据6σ设计准则计算每一代最优解的预测区间,具有较大预测区间的当前最优解即为新的高精度样本点。同时,在优化过程中序贯更新层次Kriging模型,提高最优解附近的层次Kriging模型的预测精度,从而保证设计结果的可靠性。将所提出的方法应用于微型飞行器机身结构的设计优化中,以验证该方法的有效性和优越性。采用具有不同单元数的网格模型分别作为低精度分析模型和高精度分析模型,利用最优拉丁超立方设计分别选取60个低精度样本点和20个高精度样本点建立初始层次Kriging模型,采用本文方法求解并与直接采用高精度仿真模型求解的结果进行比较。结果表明,所提出的方法能够有效利用高/低精度样本点处的信息,建立高精度的层次Kriging模型;本文方法仅需要少量的计算成本就能求得近似最优解,有效提高了设计效率,为类似的结构设计优化问题提供了参考。     

Visual hierarchical clustering of supply chain using growing hierarchical self-organising map algorithm

The study identifies a need for efficient and robust visual clustering approach that can potentially deal with complex supply chain clustering problems. Based on the underlying philosophy of group technology, a growing hierarchical self-organising map algorithm (GHSOM) is proposed to identify a lower two-dimension visual clustering map that can effectively address supply chain clustering problems. The proposed approach provides optimal solutions by decomposing a large-sized supply chain problem into independent, small, manageable problems. It facilitates simple decision-making by exploring similar clusters that are represented by the neighbouring branches in the GHSOM map structure. Unlike other approaches in literature, the proposed approach can further attain good topological ordered representations of the various work order families, to be processed by clusters of supply units along with information on hierarchical sub-cell formation as identifiable from the visually navigable map. The proposed approach has been successfully applied on 16 benchmarked problems. The performance of GHSOM based on grouping efficacy measure outperformed the best results in literature.