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视频图像中的快速人体运动目标跟踪算法研究 预览
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作者 李晨 《现代电子技术》 北大核心 2019年第3期49-51,共3页
为了有效提升视频图像中人体运动目标跟踪的速度和准确性,提出一种基于改进CamShift算法和Kalman滤波器的快速运动目标跟踪算法。首先采用YCbCr颜色模型对典型CamShift跟踪算法的预处理过程进行改进,有效提高了人体运动目标检测的鲁棒... 为了有效提升视频图像中人体运动目标跟踪的速度和准确性,提出一种基于改进CamShift算法和Kalman滤波器的快速运动目标跟踪算法。首先采用YCbCr颜色模型对典型CamShift跟踪算法的预处理过程进行改进,有效提高了人体运动目标检测的鲁棒性。然后通过结合Kalman滤波器实现运动目标的位置预测。仿真实验结果显示,相比其他基于CamShift的跟踪算法,提出的算法能够有效抑制噪声和背景的干扰,在目标跟踪的效果和准确性上均有一定的提高。 展开更多
关键词 目标跟踪 OPENCV KALMAN CAMSHIFT 人体目标 颜色模型
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改进的卡尔曼滤波与均值漂移目标跟踪算法
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作者 韩明 唐心亮 +1 位作者 孟军英 王敬涛 《战术导弹技术》 北大核心 2019年第1期115-123,共9页
为了实现更加理想的运动目标跟踪,提出了改进的卡尔曼滤波与均值漂移目标跟踪算法。该算法采用粒子滤波与Kalman滤波相结合实现非线性滤波,首先利用粒子滤波对运动目标的状态变量进行估计,然后对目标估计状态进行卡尔曼滤波,解决观测方... 为了实现更加理想的运动目标跟踪,提出了改进的卡尔曼滤波与均值漂移目标跟踪算法。该算法采用粒子滤波与Kalman滤波相结合实现非线性滤波,首先利用粒子滤波对运动目标的状态变量进行估计,然后对目标估计状态进行卡尔曼滤波,解决观测方程为非线性的问题。最后利用Mean-shift算法进一步聚类粒子,使抽样的粒子集更符合实际的目标概率模型,从而增加有效粒子数目,减少粒子退化。经过预测迭代,从而达到对运动目标运行轨迹的修正,并采用仿真实验进行算法性能测试。结果表明,相对于其他算法或者是传统算法,在相同的条件下该算法不仅提高了目标跟踪的精度,并且降低了计算复杂度,实时性较好。 展开更多
关键词 卡尔曼 非线性滤波 目标跟踪 均值漂移聚类 粒子滤波
Study on optimal state estimation strategy with dual distributed controllers based on Kalman filtering 预览
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作者 陈雅雯 Wang Zhuwei +2 位作者 Fang Chao Xu Guangshu Zhang Yanhua 《高技术通讯:英文版》 CAS 2019年第1期105-110,共6页
Considering dual distributed controllers, a design of optimal state estimation strategy is studied for the wireless sensor and actuator network (WSAN). In particular, the optimal linear quadratic (LQ) control strategy... Considering dual distributed controllers, a design of optimal state estimation strategy is studied for the wireless sensor and actuator network (WSAN). In particular, the optimal linear quadratic (LQ) control strategy with estimated plant state is formulated as a non-cooperative game with network-induced delays. Then, using the Kalman filter approach, an optimal estimation of the plant state is obtained based on the information fusion of the distributed controllers. Finally, an optimal state estimation strategy is derived as a linear function of the current estimated plant state and the last control strategy of multiple controllers. The effectiveness of the proposed closed-loop control strategy is verified by the simulation experiments. 展开更多
关键词 OPTIMAL state estimation STRATEGY wireless SENSOR and ACTUATOR network (WSAN) distributed controllers KALMAN filter network-induced DELAYS
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Evaluating Soil Moisture Predictions Based on Ensemble Kalman Filter and SiB2 Model
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作者 Xiaolei FU Zhongbo YU +5 位作者 Ying TANG Yongjian DING Haishen LYU Baoqing ZHANG Xiaolei JIANG Qin JU 《气象学报:英文版》 SCIE CSCD 2019年第2期190-205,共16页
Soil moisture is an important variable in the fields of hydrology, meteorology, and agriculture, and has been used for numerous applications and forecasts. Accurate soil moisture predictions on both a large scale and ... Soil moisture is an important variable in the fields of hydrology, meteorology, and agriculture, and has been used for numerous applications and forecasts. Accurate soil moisture predictions on both a large scale and local scale for different soil depths are needed. In this study, a soil moisture assimilation and prediction based on the Ensemble Kalman Filter(EnKF) and Simple Biosphere Model(SiB2) have been performed in Meilin watershed, eastern China, to evaluate the initial state values with different assimilation frequencies and precipitation influences on soil moisture predictions. The assimilated results at the end of the assimilation period with different assimilation frequencies were set to be the initial values for the prediction period. The measured precipitation, randomly generated precipitation,and zero precipitation were used to force the land surface model in the prediction period. Ten cases were considered based on the initial value and precipitation. The results indicate that, for the summer prediction period with the deeper water table depth, the assimilation results with different assimilation frequencies influence soil moisture predictions significantly. The higher assimilation frequency gives better soil moisture predictions for a long lead-time. The soil moisture predictions are affected by precipitation within the prediction period. For a short lead-time, the soil moisture predictions are better for the case with precipitation, but for a long lead-time, they are better without precipitation. For the winter prediction period with a lower water table depth, there are better soil moisture predictions for the whole prediction period. Unlike the summer prediction period, the soil moisture predictions of winter prediction period are not significantly influenced by precipitation. Overall, it is shown that soil moisture assimilations improve its predictions. 展开更多
关键词 soil moisture ENSEMBLE KALMAN Filter (EnKF) Simple BIOSPHERE MODEL (SiB2) prediction
Polarization de-multiplexing using a modified Kalman filter in CO-OFDM transmissions
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作者 江杨 易兴文 +6 位作者 胡少华 黄夏涛 唐伟 周雯静 黄新宁 张静 邱昆 《中国光学快报:英文版》 SCIE EI CAS CSCD 2019年第3期22-26,共5页
We propose the modified Kalman filter(MKF) using the received signal for observation and constructing an inverse process of the conventional Kalman filter(CKF) for polarization de-multiplexing in coherent optical(CO) ... We propose the modified Kalman filter(MKF) using the received signal for observation and constructing an inverse process of the conventional Kalman filter(CKF) for polarization de-multiplexing in coherent optical(CO) orthogonal frequency-division multiplexing(OFDM) transmissions. The MKF can avoid the convergence error problem in CKF without matrix inverse operation and has a faster converging speed and a much larger tolerance to the process and measurement noise covariance, about two orders of magnitude more than those of CKF. We experimentally demonstrate the 12 Gbaud OFDM signal transmission over 480 km standard singlemode fiber. The performance of MKF and CKF outperforms pilot-aided polarization de-multiplexing with better accuracy and nonlinearity tolerance. 展开更多
关键词 POLARIZATION de-multiplexing MODIFIED KALMAN filter CO-OFDM transmissions
Weak harmonic signal detection method in chaotic interference based on extended Kalman filter 预览
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作者 Chengye Lu Sheng Wu +1 位作者 Chunxiao Jiang Jinfeng Hu 《数字通信与网络:英文版》 2019年第1期51-55,共5页
The traditional methods of weak harmonic signal detection under strong chaotic interference often suffer from high computational complexity and poor performance. In this paper, an Extended Kalman Filter (EKF) based de... The traditional methods of weak harmonic signal detection under strong chaotic interference often suffer from high computational complexity and poor performance. In this paper, an Extended Kalman Filter (EKF) based detection method is proposed for the detection of weak harmonic signal. The EKF method avoids matrix inversion by iterating measurement equation and state equation, which simultaneously improves the robustness and reduces the complexity. Compared with the existing detection methods, the proposed method has the following advantages: 1) it has better performance than the neural network method;2) it has similar performance with the optimal filtering method, but with lower computational complexity;3) it is more robust compared with the optimal filtering method. 展开更多
关键词 Extended KALMAN filter STRONG CHAOTIC INTERFERENCE WEAK HARMONIC signal
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Model Error Correction in Data Assimilation by Integrating Neural Networks
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作者 Jiangcheng Zhu Shuang Hu +3 位作者 Rossella Arcucci Chao Xu Jihong Zhu Yi-ke Guo 《大数据挖掘与分析(英文)》 2019年第2期83-91,共9页
In this paper, we suggest a new methodology which combines Neural Networks(NN) into Data Assimilation(DA). Focusing on the structural model uncertainty, we propose a framework for integration NN with the physical mode... In this paper, we suggest a new methodology which combines Neural Networks(NN) into Data Assimilation(DA). Focusing on the structural model uncertainty, we propose a framework for integration NN with the physical models by DA algorithms, to improve both the assimilation process and the forecasting results. The NNs are iteratively trained as observational data is updated. The main DA models used here are the Kalman filter and the variational approaches. The effectiveness of the proposed algorithm is validated by examples and by a sensitivity study. 展开更多
关键词 data ASSIMILATION deep learning neural networks KALMAN filter VARIATIONAL approach
黄海海雾短时临近预报中云水路径的EnKF同化研究 预览
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作者 高小雨 高山红 《海洋与湖沼》 CAS CSCD 北大核心 2019年第2期248-260,共13页
在海雾的短时临近预报中,初始场的水汽凝结状态扮演着重要角色。为了改进初始场的云水含量,本文提出直接同化雾体云水信息的思路。针对2011年5月一次大范围的黄海海雾,借助EnKF (Ensemble Kalman Filter)方法,尝试进行了极轨卫星反演云... 在海雾的短时临近预报中,初始场的水汽凝结状态扮演着重要角色。为了改进初始场的云水含量,本文提出直接同化雾体云水信息的思路。针对2011年5月一次大范围的黄海海雾,借助EnKF (Ensemble Kalman Filter)方法,尝试进行了极轨卫星反演云水路径数据的同化试验。结果表明:(1)通过利用EnKF 将云水混合比增加到背景场和分析场的控制变量中,构建云水观测数据与背景场之间的关系,实现云水路径数据的直接同化是可行的;(2)同化云水路径可显著改善海面气温与湿度状态,大幅提高海雾预报效果;(3)EnKF能够基于集合体动态统计流依赖的背景误差协方差是其取得良好同化效果的主要原因。值得指出的是,受集合样本误差的影响,需要特别关注云水含量与风之间的相关关系。 展开更多
关键词 黄海海雾 短时临近预报 EnKF(Ensemble KALMAN Filter)同化 云水路径 海雾雾区
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Full waveform inversion based on the ensemble Kalman filter method using uniform sampling without replacement
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作者 Jian Wang Dinghui Yang +1 位作者 Hao Jing Hao Wu 《科学通报:英文版》 SCIE EI CSCD 2019年第5期321-330,共10页
Full waveform inversion(FWI)has been increasingly more and more important in seismology to better understand the interior structure of the Earth.FWI,by taking advantage of both the traveltime and amplitude in the data... Full waveform inversion(FWI)has been increasingly more and more important in seismology to better understand the interior structure of the Earth.FWI,by taking advantage of both the traveltime and amplitude in the data,provides high-resolution model parameters of the earth which can produce images with high resolution.However,this inversion method conventionally suffers from non-uniqueness due to many local minima of the objective function and large computing costs.In this study,we propose a new FWI method in a semi-random framework by integrating the ensemble Kalman filter and uniform sampling without replacement.Numerical results demonstrate that the new method can achieve highresolution results and a wider convergence domain.Accordingly,the new method overcomes the disadvantage of conventional FWIs that depend strongly on the initial model. 展开更多
关键词 Data ASSIMILATION ENSEMBLE KALMAN filter UNIFORM sampling without replacement Full WAVEFORM INVERSION
Distributed adaptive Kalman filter based on variational Bayesian technique
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作者 Chen HU Xiaoming HU Yiguang HONG 《控制理论与技术:英文版》 EI CSCD 2019年第1期37-47,共11页
In this paper, distributed Kalman filter design is studied for linear dynamics with unknown measurement noise variance, which modeled by Wishart distribution. To solve the problem in a multi-agent network, a distribut... In this paper, distributed Kalman filter design is studied for linear dynamics with unknown measurement noise variance, which modeled by Wishart distribution. To solve the problem in a multi-agent network, a distributed adaptive Kalman filter is proposed with the help of variational Bayesian, where the posterior distribution of joint state and noise variance is approximated by a free-form distribution. The con vergence of the proposed algorithm is proved in two main steps: n oise statistics is estimated, where each age nt only use its local information in variational Bayesian expectation (VB-E) step, and state is estimated by a consensus algorithm in variational Bayesian maximum (VB-M) step. Finally, a distributed target tracking problem is investigated with simulations for illustration. 展开更多
关键词 DISTRIBUTED KALMAN FILTER adaptive FILTER MULTI-AGENT system VARIATIONAL BAYESIAN
Contribution of the FPGAs for Complex Control Algorithms: Sensorless DTFC with an EKF of an Induction Motor
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作者 Saber Krim Soufien Gdaim +1 位作者 Abdellatif Mtibaa Mohamed Faouzi Mimouni 《国际自动化与计算杂志:英文版》 EI CSCD 2019年第2期226-237,共12页
In a conventional direct torque control (CDTC) of the induetion motor drive, the electromagnetic torque and the stator flux are characterized by high ripples. In order to reduce the undesired ripples, several methods ... In a conventional direct torque control (CDTC) of the induetion motor drive, the electromagnetic torque and the stator flux are characterized by high ripples. In order to reduce the undesired ripples, several methods are used in the literature. Nevertheless, these methods increase the algorithm complexity and dependency on the machine parameters such as the space vector modulation (SVM). The fuzzy logic control method is utilized in this work to decrease these ripples. Moreover, to eliminate the mechanical sensor the extended kalman filter (EKF) is used, in order to reduce the cost of the system and the rate of maintenance. Furthermore, in the domain of controlling the real-time induction motor drives, two principal digital devices are used such as the hardware (FPGA) and the digital signal processing (DSP). The latter is a software solution featured by a sequential processing that increases the execution time. However, the FPGA is featured by a high processing speed because of its parallel processing. Therefore, using the FPGA it is possible to implement complex algorithms with low execution time and to enhance the control bandwidth. The large bandwidth is the key issue to increase the system performances. This paper presents the interest of utilizing the FPGAs to iinplement complex control algorithms of electrical systems in real time. The suggested sensorless direct torque control using the fuzzy logic (DTFC) of an induction motor is successfully designed and implemented on an FPGA Virtex 5 using xilinx system generator. The simulation and implementation results show proposed approach's performances in terms of ripples, stator current harmonic waves, execution time, and short design time. 展开更多
关键词 Direct torque CONTROL fuzzy logic CONTROL (FLC) extended KALMAN filter Xilinx system generator (XSG) field programmable gate array (FPGA)
Flight Safety System Evaluation and Optimal Linear Prediction 预览
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作者 DING Songbin GU Qianqian LIU Jiayu 《南京航空航天大学学报:英文版》 EI CSCD 2019年第2期205-213,共9页
The complexity of flight safety system is usually affected by a variety of uncertainties.The uncertainty of overall security situation of flight safety system are hardly determined.In this work,flight safety assessmen... The complexity of flight safety system is usually affected by a variety of uncertainties.The uncertainty of overall security situation of flight safety system are hardly determined.In this work,flight safety assessment index system is firstly established based on software hardware environment liveware management(SHELM)model.And flight safety assessment is also carried out with matter-element theory algorithm to obtain safety state.According to correlation degree values of each evaluation index,key indexes affected flight safety are obtained.Under the assumption that the flight safety system is a linear dynamic system and combining the above evaluation analysis,Kalman filter algorithm is used to carry out prediction analysis on security situation.A simulation analysis is carried out based on an actual flight safety situation of an airline.The results show that the security state of airline flight safety system in a short period of time can be obtained,and main factors affecting flight safety are found out.This provides a viable way for airlines to further strengthen flight safety management. 展开更多
关键词 FLIGHT SAFETY FLIGHT SAFETY assessment and prediction software HARDWARE environment liveware management(SHELM)model MATTER-ELEMENT THEORY KALMAN filter THEORY
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A Distributed Cooperative Localization Algorithm for Mobile Multi-platforms Oriented to Unpredicted Communication Topology 预览
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作者 WANG Leigang CUI Jianling +1 位作者 KONG Depei ZHAO Linfeng 《南京航空航天大学学报:英文版》 EI CSCD 2019年第2期224-231,共8页
The cooperative localization(CL)is affected by the communication topology among the platforms.Based on the unscented Kalman filtering,the distributed CL(DCL)oriented to the unpredicted communication topology is invest... The cooperative localization(CL)is affected by the communication topology among the platforms.Based on the unscented Kalman filtering,the distributed CL(DCL)oriented to the unpredicted communication topology is investigated.To improve the adaptability,the character of the look-up Cholesky decomposition is exploited for the covariance matrix decomposing.Then,the distributed U transformation can be dynamically implemented according to the available communication topology.In the proposed algorithm,the global information is not required for the individual,and only the available information from the neighbor is used.Each platform’s state can be estimated independently.The error covariance of the state estimates can be updated in the single platform.The algorithm is adaptive to any serial communication topologies where the measuring to the measured platform is a starting path.The applicability of the proposed algorithm to unpredicted communication topology is improved,remaining equivalent localization performance to free connection communication. 展开更多
关键词 MOBILE multi-platforms COOPERATIVE localization unscented KALMAN filtering COMMUNICATION TOPOLOGY
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A model-based prognostics method for fatigue crack growth in fuselage panels
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作者 Yiwei WANG Christian GOGU +2 位作者 Nicolas BINAUD Christian BES Jian FU 《中国航空学报:英文版》 SCIE EI CAS CSCD 2019年第2期396-408,共13页
This paper proposes a model-based prognostics method that couples the Extended Kalman Filter(EKF) and a new developed linearization method. The proposed prognostics method is developed in the context of fatigue crack ... This paper proposes a model-based prognostics method that couples the Extended Kalman Filter(EKF) and a new developed linearization method. The proposed prognostics method is developed in the context of fatigue crack propagation in fuselage panels where the model parameters are unknown and the crack propagation is affected by different types of uncertainties. The coupled method is composed of two steps. The first step employs EKF to estimate the unknown model parameters and the current damage state. In the second step, the proposed efficient linearization method is applied to compute analytically the statistical distribution of the damage evolution path in some future time. A numerical case study is implemented to evaluate the performance of the proposed method. The results show that the coupled EKF-linearization method provides satisfactory results: the EKF algorithm well identifies the model parameters, and the linearization method gives comparable prediction results to Monte Carlo(MC) method while leading to very significant computational cost saving. The proposed prognostics method for fatigue crack growth can be used for developing predictive maintenance strategy for an aircraft fleet, in which case, the computational cost saving is significantly meaningful. 展开更多
关键词 Aircraft FUSELAGE PANELS Extended Kalman filter Fatigue crack propagation LINEARIZATION METHOD MODEL-BASED PROGNOSTICS
Fault diagnosis based on measurement reconstruction of HPT exit pressure for turbofan engine
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作者 Xin ZHOU Feng LU Jinquan HUANG 《中国航空学报:英文版》 SCIE EI CAS CSCD 2019年第5期1156-1170,共15页
Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which som... Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which sometimes cannot be measured in engineering. The most typical one is the High-Pressure Turbine(HPT) exit pressure, which is vital to distinguishing failure modes between different turbines. For the case of an abrupt failure occurring in a single turbine component, a model-based sensor measurement reconstruction method is proposed in this paper. First,to estimate the missing measurements, the forward algorithm and the backward algorithm are developed based on corresponding component models according to the failure hypotheses. Then,a new fault diagnosis logic is designed and the traditional nonlinear filter is improved by adding the measurement estimation module and the health parameter correction module, which uses the reconstructed measurement to complete the health parameters estimation. Simulation results show that the proposed method can well restore the desired measurement and the estimated measurement can be used in the turbofan engine gas path diagnosis. Compared with the diagnosis under the condition of missing sensors, this method can distinguish between different failure modes, quantify the variations of health parameters, and achieve good performance at multiple operating points in the flight envelope. 展开更多
关键词 Component-level model Condition monitoring FAULT diagnosis MEASUREMENT RECONSTRUCTION TURBOFAN engines Unscented KALMAN filter
广义卡尔曼算法在船舶动力定位系统辨识中的应用 预览
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作者 张涛 《舰船科学技术》 北大核心 2019年第6期34-36,共3页
进入21世纪,人们在海洋开发方面给予了高度重视,使得海洋开发范围逐渐拓展。其中,动力定位系统具体指的就是海上漂浮物依靠自身动力,接受控制系统指令对外界干扰加以抵抗并确保船舶亦或是海洋平台始终以同一姿态停留于空间某定点位置。... 进入21世纪,人们在海洋开发方面给予了高度重视,使得海洋开发范围逐渐拓展。其中,动力定位系统具体指的就是海上漂浮物依靠自身动力,接受控制系统指令对外界干扰加以抵抗并确保船舶亦或是海洋平台始终以同一姿态停留于空间某定点位置。将动力定位系统应用于海底勘探、海底矿物质采集与海洋石油开发等海洋工程活动中,可以提供多元化的服务。自动力定位技术成功研发并应用于动力定位系统后,船舶动力定位系统在辨识方面的需求不断提高,本文将广义卡尔曼算法应用其中,不仅可以有效改善系统功能,同样可以充分发挥船舶动力定位系统作用。 展开更多
关键词 卡尔曼 定位 辨识
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基于PID+Kalman的姿态角算法研究 预览
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作者 刘春 傅丽娟 +1 位作者 谢皓 邓传远 《仪表技术与传感器》 CSCD 北大核心 2018年第2期157-161,共5页
针对车辆定位的应用场合中,低成本的惯性导航系统( INS)精度不足,以及姿态角解算中姿态角误差随时间推移而不断增长的问题,提出了一种基于 PID+kalman 的算法,对陀螺仪、加速度计信号和姿态角误差进行 PID+kalman 的融合修正,实现... 针对车辆定位的应用场合中,低成本的惯性导航系统( INS)精度不足,以及姿态角解算中姿态角误差随时间推移而不断增长的问题,提出了一种基于 PID+kalman 的算法,对陀螺仪、加速度计信号和姿态角误差进行 PID+kalman 的融合修正,实现了姿态角的短时间高精度测量和长时间稳定输出.在以 DSP 和 MPU 为核心的信号处理系统上实时实现了检测,并进行了实验. 实验结果验证了方法的有效性. 展开更多
关键词 惯性导航系统 陀螺仪 姿态角 PID KALMAN 信号处理
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Design of Intelligent Balancing Vehicle Control System based on Arduino 预览
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作者 HOU Zeyao 《国际设备工程与管理:英文版》 2018年第3期164-167,共4页
关键词 车辆控制系统 平衡设计 KALMAN 车辆速度 设计计划 微控制器 测量角度 平衡控制
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过程不确定性下丙烯精馏过程多变量预测控制技术应用 预览
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作者 何仁初 陈海泉 +1 位作者 于春梅 张卫东 《西安石油大学学报:自然科学版》 北大核心 2018年第4期102-108,共7页
以丙烯精馏塔的多变量预测控制为研究对象,将卡尔曼(Kalman)滤波方法与动态反馈预测控制技术相结合,提出了一种带有积分输入补偿的Kalman滤波方法对系统不确定性干扰进行估计,然后将滤波后的输出、控制作用及状态信息动态反馈给多变... 以丙烯精馏塔的多变量预测控制为研究对象,将卡尔曼(Kalman)滤波方法与动态反馈预测控制技术相结合,提出了一种带有积分输入补偿的Kalman滤波方法对系统不确定性干扰进行估计,然后将滤波后的输出、控制作用及状态信息动态反馈给多变量预测控制器以增强系统的抗干扰能力,提高控制系统的性能,并构建出丙烯精馏塔过程机理模型及仿真平台。仿真结果对比表明,采用本文改进的Kalman滤波方法使得多变量预测控制系统的控制性能和鲁棒性明显增强,生产过程更加平稳。 展开更多
关键词 丙烯精馏 不确定性 过程控制 KALMAN 动态反馈
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Multi-sensor optimal weighted fusion incremental Kalman smoother 预览
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作者 SUN Xiaojun YAN Guangming 《系统工程与电子技术:英文版》 SCIE EI CSCD 2018年第2期262-268,共7页
In practical applications,the system observation error is widespread.If the observation equation of the system has not been verified or corrected under certain environmental conditions,the unknown system errors and fi... In practical applications,the system observation error is widespread.If the observation equation of the system has not been verified or corrected under certain environmental conditions,the unknown system errors and filtering errors will come into being.The incremental observation equation is derived,which can eliminate the unknown observation errors effectively.Furthermore,an incremental Kalman smoother is presented.Moreover,a weighted measurement fusion incremental Kalman smoother applying the globally optimal weighted measurement fusion algorithm is given.The simulation results show their effectiveness and feasibility. 展开更多
关键词 weighted fusion INCREMENTAL KALMAN FILTERING POOR observation condition KALMAN smoother global OPTIMALITY
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