Strong tracking adaptive Kalman filters for underwater vehicle dead reckoning

To improve underwater vehicle dead reckoning, a developed strong tracking adaptive kalman filter is proposed. The filter is improved with an additional adaptive factor and an estimator of measurement noise covariance. Since the magnitude of fading factor is changed adaptively, the tracking ability of the filter is still enhanced in low velocity condition of underwater vehicles. The results of simulation tests prove the presented filter effective.     

The stabilization control of underactuated surface vessels

The problem of stabilization control of underactuated surface vessels with two independent control inputs is in vestigated inthis paper. Through transformation, a cascade property of the system is revealed. And the original nonlinear system could be divided into two subsystems: a linear subsystem and a nonlinear subsystem. The stabilization laws are derived for the two subsystems separately. A smooth time - varying feedback stabilization law with exponentially convergence rate is obtained. The proposed stabilization law guarantees all the system states converge to the equilibrium exponentially. The aim of stabilization control of underactuated surface vessels is achieved. At last, the effectiveness of the proposed algorithm is illustrated by simulation tests.     

Application of data fusion method to fault diagnosis of nuclear power plant

The work condition of nuclear power plant (NPP) is very bad, which makes it has faults easily. In order to diagnose the faults real time, the fusion diagnosis system is built. The data fusion fault diagnosis system adopts data fusion method and divides the fault diagnosis into three levels, which are data fusion level, feature level and decision level. The feature level uses three parallel neural networks whose structures are the same. The purpose of using neural networks is mainly to get basic probability assignment (BPA) of D-S evidence theory, and the neural networks in feature level are used for local diagnosis, D-S evidence theory is adopted to integrate the local diagnosis results in decision level. The reactor coolant system is the study object and we choose 2# steam generator Utubes break of the reactor coolant system as a diagnostic example, The experiments prove that the fusion diagnosis system can satisfy the fault diagnosis requirement of complicated system, and verify that the fusion fault diagnosis system can realize the fault diagnosis of NPP on line timely.     

A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system

Joint power control has advantages of multi-user detection and power control;and it can combat the multi-access interference and the near-far problem. A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system was designed. Simulation results show that the algorithm can control the power not only quickly but also precisely with a time change. The method is useful for increasing system capacity.     

Application of large eddy simulation in the performance study of wave blocker

The configuration and aerodynamic performance of the inlet system are important aspects in the process of installing a gas turbine on a naval vessel. Under the requirements, large eddy simulation （LES） is used to simulate the three-dimensional fluid flow in the wave blocker of a marine inlet filter. The Smagorinsky-Lilly sub-grid model was used to model motions of small-scale structures. During numerical simulation, the SIMPLE algorithm was applied. The central-differencing spatial discretization scheme and the second order accuracy finite difference for the temporal discretization were used. Simulation gives satisfactory distribution of the vorticity fields and turbulent kinetic energy. Compared with the k-ε turbulent model, the results of LES are better for the distribution of parameters. The results of experimental study in a small-scale wind tunnel indicate that numerical calculation has higher accuracy. Therefore, the methods used are worthy of reference and introduction for the design of an inlet system.     

A nonlinear model reference adaptive inverse control algorithm with pre-compensator

In this paper, the reduced-order modeling （ROM） technology and its corresponding linear theory are expanded from the linear dynamic system to the nonlinear one, and H∞ control theory is employed in the frequency domain to design some nonlinear system＇ s pre-compensator in some special way. The adaptive model inverse control （AMIC）theory coping with nonlinear system is improved as well. Such is the model reference adaptive inverse control with pre-compensator （PCMRAIC）. The aim of that algorithm is to construct a strategy of control as a whole. As a practical example of the application, the nunlerical simulation has been given on matlab software packages. The numerical result is given. The proposed strategy realizes the linearization control of nonlinear dynamic system. And it carries out a good performance to deal with the nonlinear system.     

Application of H∞ filtering in the initial alignment of strapdown inertial navigation system

In this paper , the principle of H∞ filtering is discussed and H∞ filter is constructed, which is used in the initial alignment of the strapdown inertial navigation systems(SINS). The error model of SINS is derived. By utilizing constructed H∞ filter, the filtering calculation to that system has been conducted. The simulation results of the misalignment angle are given under the condition of unknown noises. The results show that the process of alignment with H∞ filter is much faster and with excellent robustness.     

带吊舱水下机器人运动建模与仿真(英文)

To provide a simulation system platform for designing and debugging a small autonomous underwater vehicle’s (AUV) motion controller, a six-degree of freedom (6-DOF) dynamic model for AUV controlled by thruster and fins with appendages is examined. Based on the dynamic model, a simulation system for the AUV’s motion is established. The different kinds of typical motions are simulated to analyze the motion performance and the maneuverability of the AUV. In order to evaluate the influences of appendages on the motion performance of the AUV, simulations of the AUV with and without appendages are performed and compared. The results demonstrate the AUV has good maneuverability with and without appendages.     

ISS-based robust adaptive fuzzy algorithm for maintaining a ship＇s track

This paper focuses on the problem of linear track keeping for marine surface vessels. The influence exerted by sea currents on the kinematic equation of ships is considered first. The input-to-state stability （ISS） theory used to verify the system is input-to-state stable. Combining the Nussbaum gain with backstepping techniques, a robust adaptive fuzzy algorithm is presented by employing fuzzy systems as an approximator for unknown nonlinearities in the system. It is proved that the proposed algorithm that guarantees all signals in the closed-loop system are ultimately bounded. Consequently, a ship＇s linear track-keeping control can be implemented. Simulation results using Dalian Maritime University＇s ocean-going training ship ＇YULONG＇ are presented to validate the effectiveness of the proposed algorithm.     

ISS-based robust adaptive fuzzy algorithm for maintaining a ship's track

This paper focuses on the problem of linear track keeping for marine surface vessels. The influence exerted by sea currents on the kinematic equation of ships is considered first. The input-to-state stability(ISS) theory used to verify the system is input-to-state stable. Combining the Nussbaum gain with backstepping techniques,a robust adaptive fuzzy algorithm is presented by employing fuzzy systems as an approximator for unknown nonlinearities in the system. It is proved that the proposed algorithm that guarantees all signals in the closed-loop system are ultimately bounded. Consequently,a ship's linear track-keeping control can be implemented. Simulation results using Dalian Maritime University's ocean-going training ship 'YULONG' are presented to validate the effectiveness of the proposed algorithm.     

基于渐消记忆自适应滤波的船舶动力定位算法仿真

由于船舶在海上运动的复杂性和非线性,精确的船舶动力定位系统数学模型难以建立.为了实现有效的动力定位控制,需要应用一定的状态估计滤波算法得到所需的船舶运动低频信号.采用常规的Kalman滤波,状态变量的新测量值对预测值的修正作用下降,旧测量值的影响随着计算步数的累积而相对提高,这是引起滤波发散的主要原因之一.文章针对船舶动力定位系统中使用常规的Kalman滤波而存在的模型不精确、 不能准确表达系统噪声和测量噪声等问题,采用渐消记忆自适应滤波估算低频运动信息,在状态估计算法中引入渐消记忆因子,减小旧测量值对状态估计值的影响权重,从而增大新测量值的作用;并根据滤波发散判断准则,选择适当的渐消记忆因子值来抑制滤波器的发散,使控制器输出较为平稳,从而降低推力系统不必要的能耗.仿真实验表明,所设计的自适应滤波器的收敛性、跟踪性优于常规的Kalman滤波,有效地提高了系统的定位精度和稳定性.     

GPS动态定位中自适应卡尔曼滤波模型的建立及其算法研究

采用描述机动载体运动的“当前”统计模型，建立了一种新的ＧＰＳ动态定位自适应卡尔曼滤波模型。为了进一步提高滤波器的动态性能，提出一种改进的自适应滤波算法，大大提高了ＧＰＳ动态定位卡尔曼滤波器的跟踪能力，改善了滤波效果。计算机仿真结果验证了该算法的有效性。     

面向智能船舶的容错卡尔曼融合估计方法

针对智能船舶多传感器系统因未知海洋环境干扰和设备间干扰等因素导致的一个或数个传感器产生随机间歇性故障从而导致融合估计结果出现偏差甚至失真的问题,设计1种基于四分位滤波的容错方法,并针对该方法导致的观测时滞问题设计1种预报方法,提前预报观测值,进而抵消容错方法导致的时滞问题。此外,针对多传感器之间的互协方差难以准确估计的问题,采用CI融合估计方法进行融合估计。为验证算法的有效性和融合估计的精度,对带有间歇性故障的两传感器系统进行仿真试验,并与按矩阵、按对角阵和按标量3种分布式融合估计方法得到的结果进行对比。4种方法的均方误差系数大小对比结果显示,对于带间歇性故障的多传感器系统,设计的融合滤波不仅具有鲁棒性,而且具有较高的融合精度。     

基于时延数据融合的港口船舶监控策略研究

在对现有港口船舶航行监控方法以及导航技术详细分析的基础上,结合基于Kalman滤波的数据融合技术,讨论了利用雷达、GPS以及AIS数据进行港口船舶导航算法和监控策略的设计问题。针对现有的时延平滑估计存在的缺点,提出一种基于时延的集中式预测估计融合算法。新算法具有很高的实时性和可实施性,同时,将新算法与现有的时延平滑估计融合算法相集成,提出一种完整的船舶导航和监控策略,计算机仿真算例验证了新算法的优越性,同时显示了新监控策略的有效性。     

基于加速度估计的复合导引头机动目标跟踪算法

信息融合算法是毫米波/红外复合导引头的关键技术之一,其中机动目标跟踪能力直接系统的跟踪性能。α-β作为一种常增益滤波器对CV或CA运动目标有良好的跟踪性能,但当目标机动时性能却大大下降。针对机动情况,提出一种目标加速度估计方法,并利用此加速度估计值来修正目标状态估计值,使其具有良好的机动跟踪性能。最后应用Matlab软件进行仿真分析,分析结果表明改进后的滤波器无论是对目标机动还是非机动跟踪性能良好,计算量少。     

一种自适应Morlet小波包络解调的弱故障检测方法

为自适应实现Morlet小波与故障冲击特征成分的最优匹配,采用基于Shannon小波熵的方法优化带宽参数设计了最优Morlet小波。针对最佳尺度的求取难题,利用谱峭度与小波熵均能敏感反映冲击性的特性,提出了基于峭熵比的最佳尺度的求取方法。基于此,提出基于自适应Morlet小波包络解调的弱故障特征提取方法。仿真实验与实例分析表明:该方法克服了传统包络解调需要人为设定带通滤波器参数的不足,减少人工干预,能自动有效地从强噪背景中提取微弱故障特征,具有一定的工程应用价值。     

基于数据融合的船舶电网参数测量研究

采用单传感器的传统船舶电气参数测量方法存在很多缺陷，会受到传感器的测量噪声和电网中的电磁干扰等影响，从而影响参数测量的精度和测量结果的稳定性。为此，应用状态估计技术和多传感器数据融合理论，提出了一种新的船舶电气参数测量方法。首先建立电压和电流的状态模型，将其连续的动态方程离散化，用于数字信号处理器（DSP）中。然后采用卡尔曼滤波和无反馈分布式融合来对离散化后的采样数据进行融合，从而得到全局数据融合的最优估计。最后，经过一个周期的采集数据估计值进行有效值计算，在液晶屏中显示出来。与单个传感器的检测方法相比，该检测方法具有更高的精度和更好的稳定性。仿真结果和实验测试结果都证明了本检测方法的有效性和优越性。     

基于模型预测扩展卡尔曼滤波的动力定位状态估计

针对传统扩展卡尔曼滤波由于动力定位系统过程噪声不能自适应更新,导致滤波精度下降的问题,提出了一种模型预测扩展卡尔曼滤波算法。该算法通过比较一段时间内的量测值和预测值,估计系统噪声参数,从而实时修正系统过程噪声方差。仿真结果表明,当系统的过程噪声未知的情况下,模型预测扩展卡尔曼滤波的滤波性能明显优于传统扩展卡尔曼滤波。     

基于自适应插值的符号定时恢复算法

在分析插值滤波器和均衡器的基础上,讨论了一种自适应插值的定时恢复算法,并进行了仿真.仿真结果表明,这一方法优于拉格朗日插值算法和LMS均衡算法.该算法在完成了对定时误差的插值运算的同时,也消除了衰落引起的码间干扰,性能良好.