Design and realization of hybrid ACO-based PID and LuGre friction compensation controller for three degree-of-freedom high precision flight simulator

Three degree-of-freedom (3-DOF) high precision flight simulator is a type of key hardware-in-loop equipment in the fields of aeronautics and astronautics. The conventional Proportional–Integral–Derivative (PID) is a widely used industrial controller that uses a combination of proportional, integral and derivative action on the control error to form the output of the controller. It is well known that the undesired phenomena caused by friction can lead to overall flight simulator performance degradation or instability. This paper presents a novel kind of hybrid Ant Colony Optimization (ACO)-based PID and LuGre friction compensation controller for 3-DOF high precision flight simulator. On the basis of introduction of the basic principles of ACO, the controlling scheme design for the 3-DOF high precision flight simulator is presented. Based on the popular LuGre friction model, a novel nonlinear friction compensation controller for 3-DOF high precision flight simulator is also developed. The proposed Lyapunov function proves the robust global convergence of the tracking error. The parameters tuning of PID can be summed up as the typical continual spatial optimization problem, grid-based searching strategy is adopted in the improved ACO algorithm, and self-adaptive control strategy for the pheromone decay parameter is also adopted. Modularization design is adopted in the 3-DOF high precision flight simulator. This software can process the position and status signals, and display them on the friendly interface. Double buffer mechanism is adopted in the communication protocol between lower Industrial Personal Computer (IPC) and upper IPC. The series experimental results have verified the feasibility and effectiveness of the proposed hybrid ACO-based PID and LuGre friction compensation controller.     

一种以太网边缘扫描控制器设计方案

利用嵌入式技术开发了以太网边缘扫描控制器,该控制器实现了以太网接入功能,可以测试任何符合IEEE1149．1标准的器件、电路板和系统。     

基于LabWindows／CVI的数据库应用程序开发

LabWindows／CVI是测试领域优秀的开发软件,用于开发大型、复杂的测试软件,能获得优良的测试性能,而MicrosoftAccess的数据库开发能力也十分强大,两者的结合可以使得需要测试大量指标和处理大量测试数据的自动测试系统的开发变得更加容易。本文以某电台信号处理模块的自动测试系统的开发为例,详细说明如何在眦Windows／CVI中访问Microsoft Access制作的数据库。结果表明,由此给自动测试系统在数据处理和数据存储方面提高了数倍效率。     

低耗低剖面单层波导阵列天线研究

新型单层波导阵列天线具有低耗、低剖面、结构紧凑、实用性强等诸多优点, 在毫米波甚至太赫兹无线通信领域具有巨大应用潜力, 是当前的研究热点。 文章首先介绍了用于构建波导阵列天线的几类波导馈电网络的特点, 指出E 面波导馈电网络在毫米波应用领域的优势,接着针对E 面波导在单层并馈波导阵列天线和Butler矩阵多波束阵列天线方面的研究展开叙述,最后给出了可应用在单层波导阵列天线中的开口波导辐射单元在实现多频和圆极化等不同功能上的最新研究进展。 文章对于低耗低剖面单层波导阵列天线的发展及其应用具有参考价值。     

基于改进DWA的多无人水面艇分布式避碰算法

针对多艘无人水面艇(USV)相遇自主避碰问题,考虑可能存在异常行驶的USV,基于改进动态窗口法(DWA)提出一种包含碰撞风险检测和行驶职责划分的分布式避碰算法.首先,引入障碍物预测轨迹和权重因子改进传统DWA的距离评价函数,提高USV躲避多个动态障碍物的能力,同时,结合国际海上避碰规则(COLREGS)引入新的规则评价函数约束USV的避让动作;然后,引入期望速度和航向改进现有碰撞风险检测算法,减少因碰撞风险变化导致的轨迹波动;接着,针对COLREGS仅规定两船相遇时的行驶职责划分问题,提出一种考虑异常USV的多USV职责划分方法;最后,基于Matlab实现多USV相遇自主避碰仿真.实验结果表明,即使存在异常USV,分布式避碰算法依旧保证正常USV能够作出符合COLREGS的安全避让动作.     

多智能体系统协同控制与优化专刊序言

<正>0引言近年来,随着机器人技术、人工智能技术、无线通信和计算机技术的快速发展,控制系统的规模变得更大,控制任务也变得更加复杂,由此推动了多智能体系统的形成和发展.多智能体系统是由多个具有简单功能的智能体相互关联形成的网络系统,其中每个智能体具备一定的计算、通信、感知、学习和执行能力.这些智能体之间可通过信息交互协同合作完成特定的任务,也可协调解决智能体之间的矛盾和冲突.     

Extended sliding mode observer based robust adaptive backstepping controller for electro-hydraulic servo system: Theory and experiment

This paper firstly presents an extended sliding mode observer (ESMO) for the electro-hydraulic servo systems (EHSSs) to deal with nonlinear factors like the external disturbance, parameter uncertainties as well as unmodeled characteristics in the EHSS. The model for the EHSS is established by taking these nonlinear factors into consideration and then the statespace representation is obtained. According to the state space, the ESMO for the EHSS is presented, the equivalence principle is properly utilized to simplify the ESMO and some saturation functions are employed to eliminate high frequency interferences caused by the chattering phenomenon. Based on estimated values from the ESMO, a robust adaptive backstepping controller (RABC) is presented in detail with taking some parameter uncertainties into consideration to further improve the tracking performance. The proposed controller has the following advantages: (1) utilizing the ESMO to cope with these nonlinear factors; (2) parameter online adaptive laws are employed in the RABC design to further improve the tracking performance. In order to verify the performance of the proposed controller, an experiment bench was established. Two sine waves reference signal (one amplitude 0.01 m, 1 Hz; the other 0.015 m, 2 Hz) are employed to verify the performance of the controller. Comparative experimental results show that: (1) the tracking performance of the proposed controller is better than that of a DOs based BC, a BC and a PI controller; (2) estimation values from the ESMO contains fewer noise than two conventional disturbance observers (DOs), which will decrease the control input ripples.     

Shareability-Exclusivity Representation on Product Grassmann Manifolds for Multi-camera video clustering

With the rapid popularity of multi-camera networks, one human action is usually captured by multiple cameras located at different angles simultaneously. Multi-camera videos contain the distinct perspectives of one action, therefore multiple views can overcome the impacts of illumination and occlusion. In this paper, we propose a novel multi-camera video clustering model, named Shareability-Exclusivity Representation on Product Grassmann Manifolds (PGM-SER), to address two key issues in traditional multi-view clustering methods (MVC): (1) Most MVC methods directly construct a shared similarity matrix by fusing multi-view data or their corresponding similarity matrices, which ignores the exclusive information in each view; (2) Most MVC methods are designed for multi-view vectorial data, which cannot handle the nonlinear manifold structure hidden in multi-camera videos. The proposed PGM-SER firstly adopts Product Grassmann Manifolds to represent multi-camera videos, then simultaneously learn their shared and exclusive information in global structures to achieve multi-camera video clustering. We provide an effective optimization algorithm to solve PGM-SER and present the corresponding convergence analysis. Finally, PGM-SER is tested on three multi-camera human action video datasets and obtain satisfied experimental results.     

一种深度回声状态网络的输入尺度自适应算法

深度回声状态网络是回声状态网络与深度学习思想的结合,合理选取不同谱半径的内部状态矩阵和弱积分参数能有效增强深度回声状态网络的多尺度时域特性。利用数据可视化分析输出矩阵在不同网络层中的分布关系,发现高层网络中部分神经元处于饱和工作状态且该状态抑制了网络动态预测能力。提出一种深度回声状态网络的输入矩阵自适应算法,在对网络内部状态的均值和方差进行递推估计的基础上判断神经元饱和状态,通过自适应调整各层输入权重的值来增强神经元动态性。数值计算结果表明,基于输入尺度自适应算法的深度回声状态网络相对同等规模的单层回声状态网络对于动态系统的预测精度有成倍提升。     

Low-valence ion addition induced more compact passive films on nickel-copper nano-coatings

Ni-Cu nano-coatings were prepared by pulsed electroplating technique in the baths containing various amount of boric acid. Their microstructure, morphologies and corrosion resistance were characterized in detail. The addition of boric acid strongly influences on the microstructure of the Ni-Cu coatings. The coating with a grain size of 130 nm, obtained from the bath containing 35 g L⁻¹ boric acid, shows the highest corrosion resistance. This is attributed to the low-valence Cu ion (Cu⁺) additions in nickel oxide, which could significantly decrease the oxygen ion vacancy density in the passive film to form a more compact passive film. The higher Cu⁺ additions and the lower diffusivity of point defects (D₀) are responsible for the formation of more compact passive film on the coating obtained from the bath with 35 g L⁻¹ boric acid.