自扰动内充种式大豆精量排种器的设计与试验

为提高大豆种子在排种器的活跃度和充种性能,改善大豆播种过程中机械式排种器的工作性能,设计一种自扰动内充种式大豆精量排种器。阐述排种器的结构和工作原理,依据大豆种子的外形特征及主要物理参数,对单粒种子在型孔内的3种主要不同姿态进行分析,确定了排种盘直径为140 mm、宽度为23 mm,型孔长度为7~11 mm、宽度和深度均为8 mm;根据工作原理与结构,分析排种器在充种、清种过程中种子受到扰种片的主要作用以及对排种性能的影响,并与传统结构形式的排种盘进行对比分析。为确定排种器的最佳结构参数与转速,运用EDEM仿真软件,以排种器转速、型孔长度和扰种片长度为研究对象、以排种合格率为试验指标进行正交试验。试验结果表明,影响排种质量的因素大小依次为排种器转速、型孔长度、扰种片长度;排种器最佳结构与工作参数为转速33.8 r/min,型孔长度7.3 mm,扰种片长度7.7 mm,排种合格率为95.3%。台架试验结果表明,最优参数组合下排种合格率为94.8%,与预测值基本一致,相对误差较小仅为0.5百分点,能够满足大豆单粒播种农艺需求。

自扰动人工蜂群算法

人工蜂群(Artificial Bee Colony,ABC)算法是一种模仿蜂群寻找蜜源的新型算法,因具有参数简单、灵活性强等优点而被广泛用于解决工程问题。但该算法在早熟、收敛速度慢和个体越界等缺点。为此,提出一种自扰动人工蜂群算法(Novel Artificial Bee Algorithm with Adaptive Disturbance,IGABC)。该算法采用轴对称策略处理蜂群中的越界个体,提高了算法的搜索效率。通过改进全局搜索方程的结构,同时加入带阈值的线性递增策略,提出一种全新的自适应搜索方程。自适应搜索方程提高了算法的收敛精度并加快了速度。为了获得更好的全局最优解,提出一种自扰动方法对全局最优解进行扰动。选取18个基准测试函数以及近4年提出的6个改进ABC算法进行对比实验,结果表明,该算法在收敛速度和精度上均有较大的优势,尤其在处理Rosenbrock等很难寻优的复杂函数时,收敛精度提高了16个数量级。

非自渐进扰动非扩张映射公共不动点的收敛定理(英文)

通过构造逼近两个渐进扰动非扩张映射的公共不动点的一个新的迭代算法,证明了在一致凸Banach空间中的一些强弱收敛定理.

一种具有快速跟踪能力的改进RLS算法研究

为了改善固定遗忘因子RLS(Recursive least-square)算法在时变系统中的跟踪性能,提出了一种改进的RLS算法。改进的RLS算法结合了可变遗忘因子的RLS算法和自扰动RLS算法,既克服了固定遗忘因子RLS算法中跟踪速度和参数失调的矛盾,而且也避免了当参数估值趋向于参数真值时,卡尔曼增益趋于零,从而RLS算法失去对时变系统的跟踪能力的问题。最后,在MATLAB平台下,对改进后的RLS算法进行了仿真验证。仿真结果表明,算法具有较快的收敛速度和跟踪速度以及较小的稳态误差。

基于智能天线的改进型SPRLS算法研究

针对SPRLS算法在误差较小时收敛速度慢的问题,利用误差梯度信息对自扰动项进行修正,从而提出了一种适合智能天线的改进型SPRLS算法。通过仿真试验,验证了在信道发生突变时,改进后的算法在有限迭代次数下,具有比SPRLS算法更好的收敛速度和更小的均方误差。同时该算法在复杂度上代价较小,具有较好的实用性。

多策略人工兔算法优化粒子滤波的SLAM精度研究

针对传统粒子滤波算法(particle filter,PF)重采样导致粒子贫乏,以及需增加粒子数提高估计精度的问题,提出一种基于多策略人工兔算法优化的粒子重组滤波算法。引入中垂线算法提高人工兔算法收敛速度,通过其觅食与隐藏机制,使得最优粒子引导粒子集向高似然区域移动,以此提高估计精度;实时计算最优粒子附近的粒子密度,当密度大于设置的阈值时,自适应调整迭代次数,当大于最大密度值时,引入自扰动策略避免陷入局部最优以及增加样本多样性;重采样阶段,将筛选后保留的粒子与剩余粒子重新组合成新的粒子,以此增加粒子多样性。通过仿真检验改进算法在SLAM中的性能,结果表明:该算法与其他3种算法相比,位姿与路标估计精度更高,鲁棒性更佳。

多策略融合的改进樽海鞘群算法

为解决传统樽海鞘群算法(SSA)收敛精度低、难以跳出局部最优等问题,提出了一种多策略融合的改进樽海鞘群算法(ISSA)。首先,提出了一种新的融合中垂线算法收敛策略的追随者位置更新方法,以解决传统SSA追随者位置更新方法的不足;为提升SSA跳出局部最优的能力,提出一种基于中垂线算法收敛策略的自扰动策略。其次,通过分析传统SSA领导者位置更新策略存在的不足,提出了一种新的领导者位置更新策略,并针对SSA的固定种群顺序,提出了以适应度为指标重构樽海鞘群体排列顺序的方法以提升算法性能。最后以仿真实验对ISSA的性能进行了验证,结果表明ISSA解决了SSA收敛精度低和难以跳出局部最优的问题,提升了SSA的收敛速度和稳定性。通过与其他改进SSA的对比实验,证明了ISSA的优越性。

基于改进量子粒子群优化支持向量机的变压器故障诊断方法

为了弥补量子粒子群算法优化支持向量机(QPSO-SVM)在变压器故障诊断中“早熟”收敛的不足,该文提出一种基于改进量子粒子群优化支持向量机算法。通过计算每一代粒子的平均适应值偏离度Δ并引入自扰动算子使“早熟”粒子主动跳出当前局部最优区域,增强算法的全局搜索能力。此外,建立基于所提算法的故障分类模型,对变压器故障样本进行诊断。实例结果表明:相较传统QPSO-SVM算法,改进QPSO-SVM算法可以使粒子主动跳出最优局部范围,且对变压器故障的诊断准确率更高,验证了该文方法在变压器故障诊断方面的有效性与准确性。

2.4 kbps MELP标准编码的量化性能优化

现如今通信信道环境日益复杂,因此对低速率语音编码的要求逐步提高,在保证合成语音质量的前提下降低编码速率有着重大的意义。在2.4 kbps MELP标准编码的比特分配中,LSF参数占据了很大的比重。本文将自适应多速率语音编码中的LSF参数量化技术应用在MELP编码中,并且提出了一种基于高斯自扰动的码书训练方法,对已有性能较好的量化码书添加适当的高斯自扰动作为训练数据,通过训练获得尺寸缩小的较好码书。通过实验验证,改进的MELP在1.84 kbps上效果良好。

A new detector in EBPSK communication system

In order to raise the detection precision of the extended binary phase shift keying （EBPSK） receiver, a detector based on the improved particle swarm optimization algorithm （IMPSO） and the BP neural network is designed. First, the characteristics of EBPSK modulated signals and the special filtering mechanism of the impacting filter are demonstrated. Secondly, an improved particle swarm optimization algorithm based on the logistic chaos disturbance operator and the Cauchy mutation operator is proposed, and the EBPSK detector is designed by utilizing the IMPSO-BP neural network. Finally, the simulation of the EBPSK detector based on the MPSO-BP neural network is conducted and the result is compared with that of the adaptive threshold-based decision, the BP neural network, and the PSO-BP detector, respectively. Simulation results show that the detection performance of the EBPSK detector based on the IMPSO-BP neural network is better than those of the other three detectors.

Research on PCC Control Method for Ribbon-free Random Winding

Based on analyzing the overlap appearance of random winding, basic principles of ribbon-free random winding and parametric selections for anti-overlap are discussed. The ribbon-free random winding control system and its related hardware construction as well as its software design are introduced by applying PCC technology to high speed spinning machine of synthetic filament.

Enabling Technology of Multiagent Manufacturing System:A Novel Mode of Self-organizing IoT Manufacturing

As the manufacturing mode focuses more on network and community,the orders and production processes are becoming highly dynamic and unpredictable.The traditional manufacturing system cannot handle those exceptional events such as rush orders and machine breakdowns.Nevertheless,the multiagent manufacturing system(MAMS)becomes a critical pattern to deal with these disturbances in a real-time way.However,due to the lack of universality,MAMS is difficult to be applied to industrial sites.A new multiagent architecture and the relay cooperation model based on a positive process relation matrix are proposed to address this paper’s issue.An optimized contract net protocol(CNP)-based negotiation mechanism is developed to improve the efficiency of collaboration in the proposed architecture.Finally,a case study of self-organizing internet of things(Io T)manufacturing system is used to test the feasibility and effectiveness of the method.It is shown that the proposed self-organizing Io T manufacturing mode outperforms the traditional manufacturing system in terms of makespan and critical machine workload balancing under disturbances through comparison.

Data⁃Based Feedback Relearning Algorithm for Robust Control of SGCMG Gimbal Servo System with Multi⁃source Disturbance

Single gimbal control moment gyroscope(SGCMG)with high precision and fast response is an important attitude control system for high precision docking,rapid maneuvering navigation and guidance system in the aerospace field.In this paper,considering the influence of multi-source disturbance,a data-based feedback relearning(FR)algorithm is designed for the robust control of SGCMG gimbal servo system.Based on adaptive dynamic programming and least-square principle,the FR algorithm is used to obtain the servo control strategy by collecting the online operation data of SGCMG system.This is a model-free learning strategy in which no prior knowledge of the SGCMG model is required.Then,combining the reinforcement learning mechanism,the servo control strategy is interacted with system dynamic of SGCMG.The adaptive evaluation and improvement of servo control strategy against the multi-source disturbance are realized.Meanwhile,a data redistribution method based on experience replay is designed to reduce data correlation to improve algorithm stability and data utilization efficiency.Finally,by comparing with other methods on the simulation model of SGCMG,the effectiveness of the proposed servo control strategy is verified.

Study on Disturbances and Its Effects on Nature Reserves

As a widespread natural phenomenon, disturbances are considered a discrete event occurring in a natural ecosystem within various spatial and temporal scales. The present paper discusses the types of disturbances and their influence on the ecologic system in nature reserves. It is shown that nature reserves are facing a great challenge dealing with these disturbances. A rational control for disturbances should be improved in order to promote the healthy development of nature reserves this could be done by enhancing the publicity and training of environment protection, coupling management with communities around and other nature reserves, effective management methods, rational planning, and supporting nature servers.

Performance Art and the Seduction of Theatricality

Born of the America of 1960s, performance art comes along as a celebration of presentation rather than re-presentation, as a display form of art, and an art form that does not admit of duplication. This paper presents a reading of the seductive power of performance art as rooted in our theatrical nature. I will address performance art as an emancipated form of the theatrical, where by ＂theatrical＂ I mean a specific mode of presentation and a specific mode of perception： the mode of presentation of the self to the social and the mode of perception of the self through the social. Performance art, I will argue, is hardly an anomaly of our time. Rather, its source of disturbance and fascination lies in the natural, though excessive manifestation of our theatrical nature. By its appeal to the shocking, the perilous, or the mundane even, this form of art confirms what Paul Woodruff has addressed as ＂the necessity of watching and being watched.＂ Performance art shows us the danger of self-presentation, the recognition of the other gaze as the self＇s greatest need and greatest fear. It needs no words. Mere action is more seductive than speech and does not accept speech in return. Once it has been performed, it is no longer. In Nietzsche＇s words, it celebrates the fleeting moment＇s ＂greatest weight.＂ As Samuel Beckett used to tell his actors, performance artists seem to tell their spectators： ＂Go on failing. Go on. Only next time, try to fail better.＂

Multiconfigurational Study of the Electronic Structure of Negatively Charged Fullerens

Multiconfigurational second order perturbation theory was employed in order to describe the ground and excited states of C60^-n. Different choices of the active spaces are discussed and the possibility to apply multiconfigurational theory to study C12o is investigated. The calculations were performed for all possible spin states （for selected charge） and show the preference of low spin state. The energy difference between two C60^-3 and pairs C60^-1- C60^-5 and C60^-2- C60^-4 shows that the probability to create a charge alternation in fullerides is small.

Inverse Perturbation Method for Inverse Eigenvalue Problem Based on Finite Element Analysis

An Inverse perturbation method is described for solving the general inverse eigenvalue problem. By taking the analysis of the rotor system as example based upon FEM, the new inverse perturbation method for structural design with specified low-order natural frequencies or frequency constraint bands is detailed as well as its complete theoretical basis. Moreover, formulations to calculate the inverse perturbation parameter ε and method to select the corresponding ε's value properly are also proposed. The proposed method is characterized in reducing frequency analysis and suitable for large and small structrual changes alike. Finally, several different numerical examples for inverse cigenvalue problem are discussed to illustrate the method, which show that this inverse perturbation method Is general and can be applied to other type of structure or dement.

Helicopter Maneuver Trajectory Tracking Control Based on Implicit Model and LADRC

To enhance the stability of helicopter maneuvers during task execution,a composite trajectory tracking controller design based on the implicit model(IM)and linear active disturbance rejection control(LADRC)is proposed.Initially,aerodynamic models of the main and tail rotor are created using the blade element theory and the uniform inflow assumption.Subsequently,a comprehensive flight dynamic model of the helicopter is established through fitting aerodynamic force fitting.Subsequently,for precise helicopter maneuvering,including the spiral,spiral up,and Ranversman maneuver,a regular trim is undertaken,followed by minor perturbation linearization at the trim point.Utilizing the linearized model,controllers are created for the IM attitude inner loop and LADRC position outer loop of the helicopter.Ultimately,a comparison is made between the maneuver trajectory tracking results of the IM‑LADRC and the conventional proportional-integral-derivative(PID)control method is performed.Experimental results demonstrate that utilizing the post-trim minor perturbation linearized model in combination with the IM‑LADRC method can achieve higher precision in tracking results,thus enhancing the accuracy of helicopter maneuver execution.

Adaptive Robust Dead-Zone Compensation Control of Electro-Hydraulic Servo Systems with Load Disturbance Rejection

A backstepping method based adaptive robust dead-zone compensation controller is pro- posed for the electro-hydraulic servo systems （EHSSs） with unknown dead-zone and uncertain system parameters. Variable load is seen as a sum of a constant and a variable part. The constant part is regarded as a parameter of the system to be estimated real time. The variable part together with the friction are seen as disturbance so that a robust term in the controller can be adopted to reject them. Compared with the traditional dead-zone compensation method, a dead-zone compensator is incor- porated in the EH$S without constructing a dead-zone inverse. Combining backstepping method, an adaptive robust controller （ARC） with dead-zone compensation is formed. An easy-to-use ARC tuning method is also proposed after a further analysis of the ARC structure. Simulations show that the proposed method has a splendid tracking performance, all the uncertain parameters can be estimated, and the disturbance has been rejected while the dead-zone term is well estimated and compensated.

The reliability of the improved e^N method for the transition prediction of boundary layers on a flat plate

The transition criterion in the improved eN method is that transition would occur whenever the velocity amplitude of disturbance reaches 1%-2% of the free stream velocity,while in the conventional eN method,the N factor is an empirical factor.In this paper the reliability of this key assumption in the improved eN method is checked by results of transition prediction by using the Parabolized Stability Equations(PSE).Transition locations of an incompressible boundary layer and a hypersonic boundary layer at Mach number 6 on a flat plate are predicted by both the improved eN method and the PSE method.Results from both methods agree fairly well with each other,implying that the transition criterion proposed in the improved eN method is reliable.