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针对观测器探测概率小于1的不完全量测情况下的水下纯方位系统的目标跟踪问题,提出了不完全量测下的基于扩展卡尔曼滤波的目标跟踪算法。首先,建立不完全量测情况下的水下纯方位目标跟踪数学模型;其次,在数据出现不完全量测时,采用前一次的更新值对缺失数据进行弥补并完成滤波;最后,采用最优理论性能下界(CRLB)和均方根误差(RMSE)这两种评价准则对此算法进行评估。仿真实验结果表明:在不完全量测下的水下纯方位系统的目标跟踪问题中,所提出的基于扩展卡尔曼滤波的目标跟踪算法在保证预期跟踪精度的前提下,具有较高的实时性。 相似文献
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基于非线性迭代滑模的欠驱动UUV三维航迹跟踪控制 总被引:2,自引:0,他引:2
为实现欠驱动无人水下航行器(Unmanned underwater vehicle, UUV)在未知海流干扰作用下的三维航迹跟踪控制, 提出一种基于工程解耦思想设计的非线性迭代滑模航迹跟踪控制器. 基于虚拟向导的方法,建立UUV空间航迹跟踪误差方程;采用迭代方法设计非线性滑模控制器, 无需对UUV模型参数不确定部分和海流干扰进行估计,避免了舵的抖振现象以及减小了稳态误差与超调问题. 仿真实验表明,设计的控制器对欠驱动UUV系统的模型参数摄动及海流干扰变化不敏感、 且设计参数易于调节,可以实现三维航迹的精确跟踪. 相似文献
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在水下目标检测和跟踪系统中,多目标方位估计算法起着重要的作用,MUSIC算法是最具代表性的方法;为了满足目标方位估计对高速实时并行处理技术的要求,针对水下阵列信号处理的实际应用,采用有效的并行算法和并行结构来减少运算量,设计并研制了一种基于4片ADSP-TS101S的多处理器并行实时处理系统;经过对算法的运算时间和方位估计的性能进行分析,表明该系统提高了处理效率,解决了阵列信号处理中大运算量的高速实时处理的问题,具有良好的方位估计性能和实时处理能力,满足工程实际需求。 相似文献
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针对纯方位目标跟踪系统中模型状态简化、系统噪声统计特性未知、目标初始距离信息不准确导致的滤波收敛时间长和滤波精度不高的问题,以自主水下机器人(Autonomous Underwater Vehicle, AUV)跟踪水下动态目标为例,提出了一种基于强跟踪平方根容积卡尔曼滤波器(Strong Tracking Square Root Cubature Kalman Filter, STFSRCKF)的纯方位目标运动分析算法。该算法在滤波过程中,利用平方根容积卡尔曼滤波器(Square Root Cubature Kalman Filter, SRCKF)完成预测更新,对于SRCKF中的每个容积点采用强跟踪滤波器(Strong Tracking Filter, STF)进行更新,设计滤波增益以抑制噪声对系统状态估计的影响,有效提高了滤波的数值稳定性,减小了状态估计误差。通过仿真分析,比较了扩展卡尔曼滤波器(Extended Kalman Filter, EKF)、无迹卡尔曼滤波器(Unscented Kalman Filter, UKF)、平方根容积卡尔曼滤波器(Square-Root Cubature Kalman Filter, SRCKF)、STFSRCKF的算法性能,实验表明所提算法具有跟踪速度快,精度高等优点。 相似文献
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针对粒子滤波运算量大的问题,提出一种基于箱粒子概率假设密度(Box-PHD)滤波的多目标视频跟踪方法.首先给出一种快速运动目标检测算法,通过阈值自动选取的帧差分法得到目标质心并作为量测,然后经箱粒子PHD滤波预测更新后,及时修正检测偏差实现多目标的跟踪和目标数目的估计;最后为所提算法设计了航迹识别步骤,通过颜色特征与纹理特征作为相似性度量,从而实现航迹识别,弥补了PHD滤波无法区分目标的不足.利用目标的特征区分出每个目标的航迹,同时进一步剔除了目标状态集中的杂波,保证了跟踪精度.箱粒子PHD滤波器不仅可以解决量测不确定性的问题,同时可以降低复杂度,减小运算量.实验表明,文中算法可以实现目标新生、消失、合并和分裂等复杂情况下的多目标视频跟踪,并实时区分不同目标的航迹,在保证跟踪效果的同时提高了实时性. 相似文献
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An optimal path synthesis problem for a moving observer that performs angular observations over a target moving uniformly along a straight line on a plane is solved. It is supposed that elevation and azimuth angles can be observed when the observer moves in space and only the azimuth angle can be observed when the observer moves on a plane. Observer’s trajectories are obtained with the help of Pontryagin’smaximum principle as numerical solutions of an optimal control problem. As a performance criterion the trace of covariance matrix of the target motion elements estimate is used. A possibility of solving the problem in real time on board for unmanned aerial vehicle is investigated. A comparison with the scenario of two unmanned aerial vehicles using is given. 相似文献
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Bong Seok Park Jin Bae Park Yoon Ho Choi 《International Journal of Control, Automation and Systems》2011,9(3):534-541
In this paper, an adaptive observer-based trajectory tracking problem is solved for nonholonomic mobile robots with uncertainties.
An adaptive observer is first developed to estimate the unmeasured velocities of a mobile robot with model uncertainties.
Using the designed observer and the backstepping technique, a trajectory tracking controller is designed to generate the torque
as an input. Using Lyapunov stability analysis, we prove that the closed-loop system is asymptotically stable with respect
to the estimation errors and tracking errors. Finally, the simulation results are presented to validate the performance and
robustness of the proposed control system against uncertainties. 相似文献
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Tairen Sun Hailong Pei Yongping Pan Hongbo Zhou Caihong Zhang 《Neurocomputing》2011,74(14-15):2377-2384
This paper addresses the robust trajectory tracking problem for a robot manipulator in the presence of uncertainties and disturbances. First, a neural network-based sliding mode adaptive control (NNSMAC), which is a combination of sliding mode technique, neural network (NN) approximation and adaptive technique, is designed to ensure trajectory tracking by the robot manipulator. It is shown using the Lyapunov theory that the tracking error asymptotically converge to zero. However, the assumption on the availability of the robot manipulator dynamics is not always practical. So, an NN-based adaptive observer is designed to estimate the velocities of the links. Next, based on the observer, a neural network-based sliding mode adaptive output feedback control (NNSMAOFC) is designed. Then it is shown by the Lyapunov theory that the trajectory tracking errors, the observer estimation errors asymptotically converge to zero. The effectiveness of the designed NNSMAC, the NN-based adaptive observer and the NNSMAOFC is illustrated by simulations. 相似文献
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在移动传感器网络中,观测器与目标的相对位置对目标的定位性能有重要的影响.为了提高目标的定位精度,提出了一种观测器运动轨迹的优化算法.算法把目标均方位置误差作为优化对象,使用扩展卡尔曼滤波器估计目标的位置.算法以目标和观测器的方位分布关系为基础,减小了观测器最优位置的搜索范围.仿真结果表明,使用多个观测器进行目标定位,滤波收敛速度快,定位误差小.最后给出了单个和多个观测器的"最优"运动规则. 相似文献
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This paper deals with the simultaneous estimation of states and unknown inputs for a class of Lipschitz nonlinear systems using only the measured outputs. The system is assumed to have bounded uncertainties that appear on both the state and output matrices. The observer design problem is formulated as a set of linear constraints which can be easily solved using linear matrix inequalities (LMI) technique. An application based on manipulator arm actuated by a direct current (DC) motor is presented to evaluate the performance of the proposed observer. The observer is applied to estimate both state and faults. 相似文献
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Robust Adaptive Gain Higher Order Sliding Mode Observer Based Control-constrained Nonlinear Model Predictive Control for Spacecraft Formation Flying
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Ranjith Ravindranathan Nair Laxmidhar Behera 《IEEE/CAA Journal of Automatica Sinica》2018,5(1):367-381
This work deals with the development of a decentralized optimal control algorithm, along with a robust observer, for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements. A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains, which will give enough flexibility in the choice of initial estimates. Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach. 相似文献
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针对三自由度全驱动船舶速度向量不可测问题,考虑船舶模型参数和外部环境扰动均未知的情况,提出一种基于神经网络观测器的船舶轨迹跟踪递归滑模动态面输出反馈控制方法.该方法设计神经网络自适应观测器估计船舶速度向量,且利用神经网络逼近模型参数不确定项,综合考虑船舶位置和速度误差之间关系构造递归滑模面,再采用动态面控制技术设计轨迹跟踪控制律和参数自适应律,并引入低频增益学习方法消除外界扰动导致的高频振荡控制信号.选取李雅普诺夫函数证明了该控制律能够保证轨迹跟踪闭环系统内所有信号的一致最终有界性.最后,基于一艘供给船进行仿真验证,结果表明,船舶轨迹跟踪响应速度快,所设计控制器对系统模型参数摄动及外界扰动具有较强的鲁棒性. 相似文献
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A. A. Galyaev E. P. Maslov E. Ya. Rubinovich 《Journal of Computer and Systems Sciences International》2009,48(3):458-464
The evasion problem of a mobile object from detection by a stationary observer in a passive mode is solved. For the case of power dependence of the level of the radiated signal on the motion velocity, a control law for velocity and the trajectory of the object that provide a minimum to the integral level of the signal coming to the observer input for the time of object motion are found in an explicit form. 相似文献
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Fouad Yacef Omar Bouhali Mustapha Hamerlain Nassim Rizoug 《Journal of Intelligent and Robotic Systems》2016,84(1-4):179-197
In this paper, an Adaptive Fuzzy Backstepping Control (AFBC) approach with state observer is developed. This approach is used to overcome the problem of trajectory tracking for a Quadrotor Unmanned Aerial Vehicle (QUAV) under wind gust conditions and parametric uncertainties. An adaptive fuzzy controller is directly used to approximate an unknown nonlinear backstepping controller which is based on the exact model of the QUAV. Besides, a state observer is constructed to estimate the states. The stability analysis of the whole system is proved using Lyapunov direct method. Uniformly Ultimately Bounded (UUB) stability of all signals in the closed-loop system is ensured. The proposed control method guarantees the tracking of a desired trajectory, attenuates the effect of external disturbances such as wind gust, and solves the problem of unavailable states for measurement. Extended simulation studies are presented to highlight the efficiency of the proposed AFBC scheme. 相似文献
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The mathematical formulation of optimal trajectory planning for a space robot docking with a moving target is derived. The calculus of variations is applied to the problem so that the optimal robot trajectory can be obtained directly from the target information without first planning the trajectory of the end-effector. The nonlinear two-point boundary value problem resulting from the problem formulation is solved numerically by a globally convergent homotopy algorithm. The algorithm guarantees convergence to a solution for an arbitrarily chosen initial guess. Numerical simulation for three examples demonstrates the approach. © 3995 John Wiley & Sons, Inc. 相似文献