Modeling of Non-Coherent Sequential Acquisition Process for DS/SS Signals

A modified non-coherent sequential detection decision logic based on continuous accumulation to achieve fast PN code acquisition is proposed. To simplify the design and analysis, the equivalent relationship between the likelihood ratio of the current sample and that of all the previous samples is deduced. The scheme is proved to be an optimum sequential detection under certain assumptions. Because the average sample number (ASN) can not be calculated through the methods applied to the conventional sequential detection, an algorithm is also provided, which can estimate both the probability density function (pdf) and the upper threshole of ASN. The desired probabilities of false alarm and detection, as well as faster PN code acquisition compared to the conventional sequential detection can be achieved by employing this structure . In addition, Rayeigh-faded reception case is also taken into consideration. Performances of the proposed schemes are obtained, which suggest that the proposed non-coherent seque     

MATTER-ELEMENT MODELING OF PARALLEL STRUCTURE AND APPLICATION ABOUT EXTENSION PID CONTROL SYSTEM

This article describes in detail a new method via the extension predictable algorithm of the matter-element model of parallel structure tuning the parameters of the extension PID controller. In comparison with fuzzy and extension PID controllers, the proposed extension PID predictable controller shows higher control gains when system states are away from equilibrium, and retains a lower profile of control signals at the same time. Consequently, better control performance is achieved. Through the proposed tuning formula, the weighting factors of an extension-logic predictable controller can be systematically selected according to the control plant. An experimental example through industrial field data and site engineers＇ experience demonstrates the superior performance of the proposed controller over the fuzzy controller.     

Applying process mining approach to support the verification of a multi-agent system

Using agent development tools to construct an agent-based system is a well applied approach.However,the development tools usually do not have the function to check the feasibility about the workflow of the agent system during it implementation stage.Therefore,to develop an evaluation approach to analyze the feasibility of a developing agent system such that the improper workflow of an agent system can be found in the early design stage is a necessary task to reduce the risk of implementation.In this research,a Petri Net(PN) based three-stage evaluation approach was developed.In the conceptual stage,the pitfall of the current agent system developing process was examined and an improvement analysis process was specified.Then,in the system design stage,an evaluation approach which extracted the process log file from a developing agent system into a PN model in terms of a process mining approach-α algorithm was proposed.This model was simulated in a PN simulation package.The agent system performance was evaluated in terms of analyzing the deadlock phenomena of the PN model.Finally,in the implementation stage,the proposed concept was implemented by using an agent developing tool JADE and a PN simulation tool CPN.An agent-based robotic assembly system was used to examine the possible deadlock of the agent system.     

Autotuning algorithm of particle swarm PID parameter based on D-Tent chaotic model

An improved particle swarm algorithm based on the D-Tent chaotic model is put forward aiming at the standard particle swarm algorithm. The convergence rate of the late of proposed algorithm is improved by revising the inertia weight of global optimal particles and the introduction of D-Tent chaotic sequence. Through the test of typical function and the autotuning test of proportionalintegral-derivative （PID） parameter, finally a simulation is made to the servo control system of a permanent magnet synchronous motor （PMSM） under double-loop control of rotating speed and current by utilizing the chaotic particle swarm algorithm. Studies show that the proposed algorithm can reduce the iterative times and improve the convergence rate under the condition that the global optimal solution can be got.     

汽车轮缸压力传感器故障重构方法研究与仿真

针对汽车液压制动系统中轮缸压力传感器的故障重构问题,建立了汽车液压制动系统的轮缸压力非线性模型。在此基础上,给出了一种基于滑模观测器的轮缸压力传感器故障重构方法,并将滑模观测器的设计问题转化为LMI求解问题。最后对轮缸压力传感器断路故障进行了仿真研究,讨论了不同增益对故障估计的影响。

Abstract：

A fault reconstruction scheme based on the sliding mode observer was proposed for the fault reconstruction of the wheel cylinder pressure sensor in the vehicle hydraulic braking system, as well as a nonlinearity model of the wheel cylinder in the hydraulic braking system. Furthermore, the design of the sliding-mode observer was converted to the solving of the LMI. In conclusion, the wheel cylinder pressure sensor open circuit fault simulation experiment and the influence on fault estimation over the different gain were proposed.     

H_ index based fault estimation for micro quad-rotor

Taking the attitude control system of micro quad-rotor as a research object, a design scheme of fault estimator based on generalized Kalman-Yakubovic-Popov （GKYP） lemma is put forward to deal with the problem of estimating multiple actuators malfunctions with couplings. Using an H_index and an appropriate algorithm, the goal of weakening the coupling can be achieved by limiting the fault frequency to a certain range, then different kinds of actuator faults can be estimated correctly. The simulations demonstrate the reliability and validity of the proposed method.     

Fault detection and diagnosis for data incomplete industrial systems with new Bayesian network approach

For the fault detection and diagnosis problem in largescale industrial systems,there are two important issues: the missing data samples and the non-Gaussian property of the data.However,most of the existing data-driven methods cannot be able to handle both of them.Thus,a new Bayesian network classifier based fault detection and diagnosis method is proposed.At first,a non-imputation method is presented to handle the data incomplete samples,with the property of the proposed Bayesian network classifier,and the missing values can be marginalized in an elegant manner.Furthermore,the Gaussian mixture model is used to approximate the non-Gaussian data with a linear combination of finite Gaussian mixtures,so that the Bayesian network can process the non-Gaussian data in an effective way.Therefore,the entire fault detection and diagnosis method can deal with the high-dimensional incomplete process samples in an efficient and robust way.The diagnosis results are expressed in the manner of probability with the reliability scores.The proposed approach is evaluated with a benchmark problem called the Tennessee Eastman process.The simulation results show the effectiveness and robustness of the proposed method in fault detection and diagnosis for large-scale systems with missing measurements.     

Polarimetric whitening filter for POLSAR image based on subspace decomposition

Speckle filtering is an indispensable pre-processing step for applications of polarimetric synthetic aperture radar （POLSAR）, such as terrain classification, target detection, etc. As one of the most typical methods, the polarimetric whitening filter （PWF） can be used to produce a minimum-speckle image by combining the complex elements of the scattering matrix, but polarimetric information is lost after the filtering process. A polarimetric filter based on subspaze decomposition which was proposed by Cu et al specializes in retrieving principle scattering characteristics, but the corresponding mean value of an image after filtering is not kept well. A new filter is proposed for improving the disadvantage based on subspace decomposition. Under the constraint that a weighted combination of the polarimetric SAR images equals to the output of the PWF, the Euclidean distance between an unfiltered parameter vector and a signal space vector is minimized so that noises can be reduced. It is also shown that the proposed method is equivalent to the subspace filter in the case of no constraint. Experimental results with the NASA/JPL airborne polarimetric SAR data demonstrate the effectiveness of the proposed method.     

Direction finding of coexisted independent and coherent signals using electromagnetic vector sensor

The existing direction of arrival (DOA) estimation algorithms based on the electromagnetic vector sensors array barely deal with the coexisting of independent and coherent signals. A two-dimensional direction finding method using an L-shape electromagnetic vector sensors array is proposed. According to this method, the DOAs of the independent signals and the coherent signals are estimated separately, so that the array aperture can be exploited sufficiently. Firstly, the DOAs of the independent signals are estimated by the estimation of signal parameters via rotational invariance techniques, and the influence of the coherent signals can be eliminated by utilizing the property of the coherent signals. Then the data covariance matrix containing the information of the coherent signals only is obtained by exploiting the Toeplitz property of the independent signals, and an improved polarimetric angular smoothing technique is proposed to de-correlate the coherent signals. This new method is more practical in actual signal environment than common DOA estimation algorithms and can expand the array aperture. Simulation results are presented to show the estimating performance of the proposed method.     

Validation methodology for distribution-based degradation model

Distribution-based degradation models (or graphical approach in some literature) occur in a wide range of applications. However, few of existing methods have taken the validation of the built model into consideration. A validation methodology for distribution-based models is proposed in this paper. Since the model can be expressed as consisting of assumptions of model structures and embedded model parameters, the proposed methodology carries out the validation from these two aspects. By using appropriate statistical techniques, the rationality of degradation distributions, suitability of fitted models and validity of degradation models are validated respectively. A new statistical technique based on control limits is also proposed, which can be implemented in the validation of degradation models’ validity. The case study on degradation modeling of an actual accelerometer shows that the proposed methodology is an effective solution to the validation problem of distribution-based degradation models.     

线控制动系统的踏板力模拟研究

汽车制动踏板力感模拟是汽车线控制动系统的重要组成部分,通过对传统制动系统进行分析得出踏板力与行程之间的关系,建立一种能够模拟传统车踏板力与踏板行程关系的踏板力模拟算法。仿真结果表明,研究的控制算法能较为精确的模拟传统车踏板力与踏板行程关系,为线控制动系统中踏板力的模拟提供了依据。     

基于遗传算法的车辆ABS在线整定PID控制及仿真

分析了ABS(防抱制动系统)PID控制方法的原理。提出了基于遗传算法的在线ABS PID控制方法。为了使控制器具有更高的搜索效率以满足ABS的实时性要求,改进了遗传算法的遗传算子,使复制与交叉操作并列存在,使用具有选择性的交叉操作,并改变变异操作的随机性,使其成为受控的随机操作。使系统能根据车辆的运行条件实时整定PID控制参数。仿真结果表明,基于遗传算法的在线ABSPID控制方法能有效抑制超调,控制ABS跟踪路面条件变化。     

基于PLPF方法的车辆ABS控制方法

建立了四通道车辆防抱制动系统（ABS）的状态空间模型，考虑到其非线性特性，提出了用PLPF（分段线性多项式）函数对其进行分段线性化的方法，并提出了修正的PLPF方法，利用车辆系统的状态参数得出系统矩阵和控制矩阵。用最优控制方法得出在下一个采样点时的车辆状态，即可按照基于PLPF的最优控制方法得到控制序列。     

虚拟场景中自动漫游路径的多分辨率规划

在三维虚拟场景中，为了避免自动生成的漫游路径所引起的视觉抖动和场景跳变现象，增强漫游的真实感，提出了一种基于样条小波的多分辨率漫游路径生成方法，详细叙述了根据自动漫游过程中通道宽度的变化采用不同的分辨率来构造漫游路径的原理和具体实现。最后，给出了一个在船舶设计三维虚拟环境中漫游的实例，进一步说明该方法能够获得更加流畅的漫游路径，使漫游中的场景变化更加连续平滑。     

The Application of Simulation Technique in Whole CIMS Life Cycle

Ｔｈｅ　Ａｐｐｌｉｃａｔｉｏｎ　ｏｆ　Ｓｉｍｕｌａｔｉｏｎ　Ｔｅｃｈｎｉｑｕｅ　ｉｎ　Ｗｈｏｌｅ　ＣＩＭＳ　Ｌｉｆｅ　ＣｙｃｌｅＸｉｏｎｇＧｕａｎｇｌｅｎｇａｎｄＧｕｏＪｉａｎｂｏ（ＤｅｐａｒｔｍｅｎｔｏｆＡｕｔｏｍａｔｉｏｎ，ＴｓｉｎｇｈｕａＵｎｉ...     

一种视频对象生成方法的研究与实现

提出了一种视频对象的自动生成方法。首先对当前帧进行全局运动估计和补偿 ,并和上一帧进行差分运算 ,然后采用模糊分类器自动检测出运动区域 ,再结合边界特征形成视频对象的二进制模型并生成视频对象。实验结果表明 ,该方法能有效地生成视频对象 ,具有较强的鲁棒性     

基于模糊AHP的视景仿真系统逼真度评估方法研究

总结了在当前视景仿真逼真度研究中存在的不足,即大多数研究都集中在评估方法上,而忽视了指标体系的作用。对此提出了一套视景仿真逼真度评估的指标体系,包括了从三维建模到仿真画面输出在内的整个视景仿真系统构建的各个步骤,并以某鱼雷视景仿真系统为例,探讨了这套指标在工程实践当中的运用,最后得出了设计和开发视景仿真系统的5条原则。     

电涡流缓速器的三维数值仿真

为三维电涡流缓速器的仿真提供了一个完全的有限元表达式,这个表达式通过运用A,Φ-A公式结合库仑定律得以实现.为了考虑电涡流缓速器不规则的几何形状,采用了四面体单元对网格进行划分,并用有限元程序仿真电涡流缓速器在500rpm的磁通密度分布.电涡流缓速器在不同转速下用有限元程序计算的制动力矩与测量值进行了比较,测量值和仿真教据近似一致,有限元程序可用于工程计算和仿真.     

用于人机交互的交流式电磁跟踪系统的研究

虚拟现实系统和计算机仿真系统中广泛采用电磁跟踪系统测量用户的头部或手部的位置和姿态来实现人机交互。本文分析了目前已有的直流式电磁跟踪系统的不足，提出了一种采用交流信号作激励源的交流式电磁跟踪系统，研究了该系统的结构，推导了用于提取传感器接收信号的递推数字互相关算法，讨论了算法参数与算法性能的关系。仿真实验证明了算法的有效性及理论分析的正确性。本文的研究成果为实际的交流式电磁跟踪系统的设计提供了理论依据。     

汽车转弯防抱制动系统中双模控制器的应用

针对当前ABS系统的分析大多集中在少自由度的直线制动方面。采用十一自由度汽车转弯制动数学模型,用MATLAB/SIMULINK建立仿真模型。考虑到此系统的非线性、时变性及工况的不确定性,采用了模糊控制算法,并对防抱死制动系统的制动过程进行了仿真研究。针对模糊控制算法的不足,建立了双模控制器,用传统的PID算法优化模糊控制器。采用的十一自由度的转弯制动模型充分考虑到仿真的复杂度及仿真的可信度,完全反应了制动过程中汽车的宏观运动及微观运动。