基于改进A^(*)算法+LM-BZS算法的农业机器人路径规划

针对目前农业机器人在全局路径规划过程中存在规划效率低、规划路径折线段多、折线角度大、作业不稳定等问题,以果园履带机器人为运动学模型,提出一种基于改进A^(*)算法+低阶多段贝塞尔曲线拼接(Low-order multi-segment Bezier curve splicing,LM-BZS)算法的路径规划方法。首先,根据先验地图获取果园环境信息,将果树和障碍物视作不可通行区域,并结合机器人本体尺寸,对不可通行区域进行膨胀拟合处理;然后,利用改进A^(*)算法搜索路径,对初步生成路径进行树行节点调整;最后,采用LM-BZS算法对调整后的路径点进行优化处理,生成符合果园履带机器人作业要求的行驶路径。仿真试验结果表明,相较于传统A^(*)算法,本文所提出的改进算法在无障碍和有障碍环境中,路径规划时间分别减少76.75%、86.40%,节点评估数量分别减少36.68%、39.37%;经LM-BZS算法优化所得路径在无障碍环境中,相较于传统A^(*)算法和高阶贝塞尔算法,平均曲率分别降低45.81%、18.94%;在有障碍环境中平均曲率分别降低56.98%、27.81%。场地试验结果表明,果园履带机器人在对本文算法生成路径进行跟踪行驶时,在无障碍和有障碍环境中,最大横向误差分别为0.428、0.491 m,平均横向误差分别为0.232、0.276 m,平均航向偏差分别为11.06°、13.76°,符合果园履带机器人自主行驶条件。

基于x-LMS算法的直升机主动消振电力作动器系统研究

直升机前飞时,气动环境会导致不同方位角的桨叶出现气动载荷的瞬间不对称,通过基础结构传递会在机身形成大幅度的低频振动。为了消除多方向幅值变化的振动力,利用结构响应主动控制原理,设计了基于x-LMS算法的主动消振电力作动器系统,并进行了减振实验。首先,通过比较确定了单台作动器中两台电机同向旋转的方案。通过两台作动器的组合使用,推导出输出力的数学模型。其次,采用负载相位差交叉耦合的控制策略设计系统控制框图。针对存在耦合的相位外环,通过回差阵特征值法确定满足系统稳定裕度要求的参数范围,再根据灵敏度函数和输入跟踪性能在所得的参数稳定域内寻找最优解。然后,提出了基于x-LMS算法的直升机主动振动控制系统,并通过仿真验证了该系统的减振效果。最后,研制的实验样机进行了动稳态实验以及减振实验,验证了系统的实际减振效果。

基于改进LM算法的冗余机器人运动学参数标定

机器人的定位精度是衡量机器人性能的重要指标,相较于重复定位精度可以从几何参数上提高几何参数,绝对定位精度还需对非几何参数进行校准。对于冗余自由度机器人,非几何参数求解更为复杂。在分析了LM算法的基础上,提出了一种基于改进LM算法的冗余机器人标定算法。首先,通过混合五参数MD-H方法建立机器人正运动学模型,采用速度级雅可比矩阵求解机器人运动学参数。实验过程中,采用深度相机对机器人末端位置进行测量。采用改进LM算法,根据测量结果对运动学参数进行校准。在改进LM算法中,通过变初始步长提高算法的适应性,并动态更新阻尼因子提高了收敛速度。改进后Quick-LM算法相较传统LM算法收敛速度提高46.7%,使机器人最大误差降低了9.18 mm,证明了改进后算法的有效性和实用性。

Adaptive inverse control of random vibration based on the filtered-X LMS algorithm

Random vibration control is aimed at reproducing the power spectral density （PSD） at specified control points. The classical frequency-spectrum equalization algorithm needs to compute the average of the multiple frequency response functions （FRFs）, which lengthens the control loop time in the equalization process. Likewise, the feedback control algorithm has a very slow convergence rate due to the small value of the feedback gain parameter to ensure stability of the system. To overcome these limitations, an adaptive inverse control of random vibrations based on the filtered-X least mean-square （LMS） algorithm is proposed. Furthermore, according to the description and iteration characteristics of random vibration tests in the frequency domain, the frequency domain LMS algorithm is adopted to refine the inverse characteristics of the FRF instead of the traditional time domain LMS algorithm. This inverse characteristic, which is called the impedance function of the system under control, is used to update the drive PSD directly. The test results indicated that in addition to successfully avoiding the instability problem that occurs during the iteration process, the adaptive control strategy minimizes the amount of time needed to obtain a short control loop and achieve equalization.

基于改进变步长LMS算法的谐波电流检测法

针对传统基于瞬时无功功率理论谐波电流检测中的二阶低通滤波器无法同时满足检测精度和响应时间的问题,提出了基于改进的双曲正切函数变步长LMS算法(IVSSLMS)的低通滤波器提取p轴和q轴中直流分量的方法;将两个谐波电流的间隔时间通过适当的调节采样间隔次数来延长,目的是为了达到高次谐波的自相关性能迅速降为零。从理论上分析了算法性能的优越,给出了参数的取值,并在simulink中搭建了仿真模型,仿真实验结果表明,改进后的低通滤波器直流分量的跟踪速度提升了一倍,得到基波正弦波形的THD值下降了0.37%。并得出以下结论:在同样输电条件下,采用改进变步长LMS算法构成低通滤波器加快了直流量的跟踪,提取的基波分量更加接近于理想波形,提升了谐波检测的瞬时性和准确性。

MI-NLMS adaptive beamforming algorithm for smart antenna system applications

A Matrix Inversion Normalized Least Mean Square (MI-NLMS) adaptive beamforming algorithm was developed for smart antenna application. The MI-NLMS which combined the individual good aspects of Sample Matrix Inversion (SMI) and the Normalized Least Mean Square (NLMS) algorithms is described. Simulation results showed that the less complexity MI-NLMS yields 15 dB improvements in interference suppression and 5 dB gain enhancement over LMS algorithm, converges from the initial iteration and achieves 24% BER improvements at cochannel interference equal to 5. For the case of 4-element uniform linear array antenna, MI-NLMS achieved 76% BER reduction over LMS algorithm.

Simplified p-norm-like Constraint LMS Algorithm for Efficient Estimation of Underwater Acoustic Channels

Underwater acoustic channels are recognized for being one of the most difficult propagation media due to considerable difficulties such as： multipath, ambient noise, time-frequency selective fading. The exploitation of sparsity contained in underwater acoustic channels provides a potential solution to improve the performance of underwater acoustic channel estimation. Compared with the classic 10 and 11 norm constraint LMS algorithms, the p-norm-like （Ip） constraint LMS algorithm proposed in our previous investigation exhibits better sparsity exploitation performance at the presence of channel variations, as it enables the adaptability to the sparseness by tuning of p parameter. However, the decimal exponential calculation associated with the p-norm-like constraint LMS algorithm poses considerable limitations in practical application. In this paper, a simplified variant of the p-norm-like constraint LMS was proposed with the employment of Newton iteration m to approximate the decimal exponential calculation. Num simulations and the experimental results obtained in physical shallow water channels demonstrate the effectiveness of the proposed method compared to traditional norm constraint LMS algorithms.

Adaptive Controller for Vehicle Active Suspension Generated Through LMS Filter Algorithms

The least means squares （LMS） adaptive filter algorithm was used in active suspension system. By adjusting the weight of adaptive filter, the minimum quadratic performance index was obtained. For two-degree-of-freedom vehicle suspension model, LMS adaptive controller was designed. The acceleration of the sprung mass,the dynamic tyre load between wheels and road,and the dynamic deflection between sprung mass and unsprung mass were determined as the evaluation targets of suspension performance. For LMS adaptive control suspension, compared with passive suspension, acceleration power spectral density of sprung mass acceleration under the road input model decreased 8-10 times in high frequency resonance band or low frequency resonance band. The simulation results show that LMS adaptive control is simple and remarkably effective. It further proves that the active control suspension system can improve both the riding comfort and handling safety in various operation conditions, and the method is fit for the active control of the suspension system.

Active micro-vibration control based on improved variable step size LMS algorithm

The contradiction of variable step size least mean square(LMS)algorithm between fast convergence speed and small steady-state error has always existed.So,a new algorithm based on the combination of logarithmic and symbolic function and step size factor is proposed.It establishes a new updating method of step factor that is related to step factor and error signal.This work makes an analysis from 3 aspects:theoretical analysis,theoretical verification and specific experiments.The experimental results show that the proposed algorithm is superior to other variable step size algorithms in convergence speed and steady-state error.

一种LM-BP加速搜索的周跳探测与修复方法

针对传统三频周跳探测与修复方法中的不敏感、漏检以及效率较低等问题,提出一种基于莱文伯格-马夸特(LM)-反向传播(BP)神经网络加速搜索法的伪距相位组合与电离层残差组合联合周跳探测与修复方法:利用2个伪距相位组合以减少不敏感周跳数量,利用1个电离层残差组合以提高小周跳探测敏感度;在构成3个线性无关的组合观测值后,使用LM-BP加速搜索算法进行周跳探测与修复。实验结果表明,相对常规的伪距相位组合与电离层残差组合联合方法,该方法能够提高周跳探测与修复性能,可探测小至1个的周跳,探测与修复整体时效有较大提升。

The implementation of Automatic Adaptive Equalizer Based on LMS Algorithm

In this paper,the inter-symbol interference and eliminating method are introduced.After analyzing the principle of adaptive equalization,we designed an adaptive equalizer using the LMS algorithm,and constructed a simulation system using MATLAB.Then we analyzed the convergence speed and mean square error characteristic of the adaptive equalizer by changing the step length factor to test the performance of the algorithm.

一种求解非线性方程组的有效Levenberg-Marquardt算法

通过修改LM参数,并结合非单调技术和信赖域技术给出一种求解非线性方程组的有效Levenberg-Marquardt算法,即AMLM算法。在局部误差界条件下,证明了AMLM算法具有局部快速收敛性。数值实验结果表明,AMLM算法稳定、有效。

Fuzzy optimization neural network model based on LM algorithm

A new fuzzy optimization neural network model is proposed based on the Levenberg-Marquardt (LM) algorithm on account of the disadvantages of slow convergence of traditional fuzzy optimization neural network model. In this new model,the gradient descent algorithm is replaced by the LM algorithm to obtain the minimum of output errors during network training,which changes the weights adjusting equations of the network and increases the training speed. Moreover,to avoid the results yielding to local minimum,the transfer function is also revised to sigmoid function. A case study is utilized to validate this new model,and the results reveal that the new model fast training speed and better forecasting capability.

融合改进LM算法及动态时间规整算法的人体动作捕捉研究

人体动作捕捉是指通过技术手段捕捉人体的运动轨迹和姿态信息,广泛应用于娱乐、体育、医疗等领域.然而,现有的动作捕捉技术存在捕捉不准确、计算效率低等问题,影响了其在实时应用场景中的表现.针对这些问题,引入一种骨骼点坐标拟合优化Levenberg-Marquardt算法,并采用粒子群算法对其加以优化.同时采用动态时间规整算法进行人体动作捕捉及评估,以期实现人体动作的实时捕捉.结果显示,该算法对肩部侧平举这一动作的捕捉准确率最高达到了99.23%,明显优于其余对比算法.此外,该算法对深蹲动作的测试时间最短,仅为1.15 s,表明该算法在进行动作捕捉时具有显著的性能优势及很强的实际应用效果,为人体动作捕捉领域提供了新的解决方案.

基于LM方法的麻花钻刃带宽度测量研究

提出一种基于二值化的麻花钻刃带宽度检测方法。首先对目标边缘进行锐化,然后用巴特沃斯高通滤波提取边缘信息;其次通过改进的大津二值化算法对疑似边缘点进行阈值分割,获取边缘点坐标;再次使用列文伯格-马夸尔特(LM)方法对边缘附近的点进行拟合,得到刃带宽度曲线并求其拐点,求取麻花钻刃带宽度的数据。最后进行对比实验,用LM方法对未处理的M35直径2.5 cm的刃带图像进行处理得到刃带宽度1.467 mm,测量误差0.467 mm。改进后的测量结果为0.853 mm,测量误差为0.147 mm。

Study of Variable Step Size LMS Adaptive Algorithm Based on Variable Region

This paper puts forward a new variable step size LMS adaptive algorithm based on variable region. The step size p（k） in the algorithm varies with the variation of the region of deviation e （k） to ensure the optimization of the three performance objectives including initial convergent speed, trace ability of the time-varying system and steady disregulation. The paper demonstrates the convergence of the algorithm accompanied by random noise,

Modified Levenberg-Marquardt algorithm for source localization using AOAs in the presence of sensor location errors

In this paper,by utilizing the angle of arrivals(AOAs) and imprecise positions of the sensors,a novel modified Levenberg-Marquardt algorithm to solve the source localization problem is proposed.Conventional source localization algorithms,like Gauss-Newton algorithm and Conjugate gradient algorithm are subjected to the problems of local minima and good initial guess.This paper presents a new optimization technique to find the descent directions to avoid divergence,and a trust region method is introduced to accelerate the convergence rate.Compared with conventional methods,the new algorithm offers increased stability and is more robust,allowing for stronger non-linearity and wider convergence field to be identified.Simulation results demonstrate that the proposed algorithm improves the typical methods in both speed and robustness,and is able to avoid local minima.

An improved WPM interference rejection system using an adaptive LMS algorithm

Based on the good time-frequency localization of the wavelet packet modulation （WPM） system and the analysis of the muhitone （MT） interference, an improved WPM narrow band interference （NBI） rejection system using an adaptive least mean square （LMS） algorithm is discussed in this paper. In the WPM interference rejection system, according to the structure of the wavelet packet tree （WFF） and the characteristic of the MT interference, the demodulated WPM signal which contains the interference component is filtered using an adaptive LMS filtering implementation. Theoretical analysis and simulation resuits show that the proposed method improves the bit error rate （BER） performance of the WPM system in the presence of MT interference.

基于改进指数优化与迭代加权LM法的机器人标定方法

针对协作机器人的出厂标定过程步骤繁琐,效率低下的问题,提出了一种基于两步策略的运动学标定算法,通过结合改进指数优化算法和迭代加权LM算法,简化标定流程并提高定位精度。首先,基于改进DH方法与位置微分误差变换建立机器人参数辨识模型,结合测量装置坐标系搭建标定系统误差模型,利用改进指数优化算法快速获取测量坐标系初始参数;其次,为提高辨识结果的鲁棒性,将距离残差作为权值因子,通过迭代加权LM算法补偿机器人模型的几何参数误差和测量坐标系矩阵参数误差;最后,通过实验验证,结果表明机器人位置误差的平均值、均方差误差和最大误差分别降低了80.28%、71.61%和52.16%,验证了该方法的正确性和有效性。

基于LM-BP神经网络的办公建筑逐时空调能耗预测

利用LM算法对BP神经网络进行改进,以提高模型收敛速度,减少迭代次数,并分别对夏季、冬季空调能耗模拟数据进行样本训练和测试,构建了LM-BP神经网络的办公建筑逐时空调能耗预测模型。结果表明夏季模型的预测值和模拟值之间的MAPE误差平均为5.74%,冬季模型的MAPE误差平均为5%,其误差均在10%以内,说明LM-BP神经网络在建筑空调能耗预测方面的可行性。并以成都地区某办公建筑实际空调能耗数据为基础对该模型进行了验证,其预测值与实际值平均相对误差为6.6%,说明建立的能耗预测模型能够满足实际工程的需要,准确的用电预测数据可为办公建筑用电侧进行实际电力市场交易提供科学的决策依据。