Sensor nodes in Internet of Things (IoT) systems are typically constrained by limited resources, such as limited computational capability, restricted storage capacity, and limited battery power, while also being vulnerable to various network attacks. To enhance the security of sensor nodes, this paper proposes a gas sensor fabricated using Cr2O3-SnO2 nanomaterials and exploits the inherent random process variations introduced during the fabrication of semiconductor gas sensors to generate physical unclonable function (PUF) responses. Response data from the Cr2O3-SnO2 gas sensors are collected under different operating conditions. To further improve the stability and uniqueness of the generated responses, a PUF response generation algorithm based on block-mapped random projection is proposed, which ultimately produces 128-bit PUF responses. The security and reliability of the proposed PUF are then evaluated. Experimental results show that the sensor-based PUF achieves a uniqueness of 50.02%, a randomness of 98.83%, and an average reliability of 97.21%. Moreover, under the assumption that an attacker has access to challenge-response pairs (CRPs) of different scales, the average prediction accuracies of the eight machine learning models remain close to 0.5. These results demonstrate that the proposed PUF exhibits strong resistance to attacks and environmental disturbances, and can enable secure and reliable identity authentication and key management services for IoT nodes.

To address the nonlinear drift challenge of gas sensors under wide temperature ranges in the Industrial Internet of Things (IoT), this article proposes a Chaotic Dynamic Harris Hawk Optimization-based Mixture of Experts (CDHHO-MoEs) temperature compensation model. First, gas sensors are fabricated, and an MoE architecture is designed by incorporating their temperature-dependent characteristics, where a temperature-aware attention mechanism is introduced to enhance thermal sensitivity. A multistrategy hybrid chaotic Harris Hawk optimization algorithm is further developed to improve the parameter optimization capability of the MoE model. Finally, benchmark tests on an STM32H743 microcontroller demonstrate that the proposed model achieves ultra-fast inference speed and high compensation accuracy, showing significant potential for IoT applications.

In this paper, we address the target localization problem based on hybrid range and angle measurements with unknown transmit power in both noncooperative and cooperative scenarios, respectively. By analyzing the approximate expressions of the noise terms in the measurement models, an original nonconvex localization problem is formulated according to the least square criterion. This problem is transformed into a mixed semi-definite programing/second-order cone programing by using convex relaxation techniques. Computer simulation results verify that the proposed algorithm can effectively solve the localization problem with good performance in the unknown transmit power case.

Impulse noise (IN) widely exists in many communication systems, which seriously affects the performance of OFDM communication systems. A joint channel and IN estimation method based on all subcarriers is designed. This method uses a sparse Bayesian learning (SBL) algorithm incorporating forward–backward Kalman filter (FB-Kalman) to tackle the problem of joint channel and IN estimation and data detection for OFDM systems. Firstly, the channel impulse response and IN are regarded as unknown sparse vectors, and a SBL framework using all subcarriers is proposed to estimate the unknown vector. The SBL theory is used based on the prior distribution of variables, and then the forward–backward joint system is established, which applies the data detection simultaneously. We also propose the FB-Kalman implementation algorithm by using the expectation maximization updates. Explicit expressions of mean and covariance matrix of the posterior distribution are derived in the E-step. Simulation results show that the proposed algorithm improves the normalized mean square error and bit error rate performance of OFDM system in the presence of IN communication environment.

本文研究了非合作环境下基于差分接收信号强度(DRSS)的定位问题.首先,建立基于DRSS测量模型的目标位置信息的优化问题.由于该非线性优化问题是非凸的,求解十分困难,为此通过半正定松弛理论,将原始的非凸优化问题转换为一种凸优化问题,由此能够快速得到原问题的一个次优解;然后,设计了非合作情形下通过对路径损耗因子和目标位置交替求解的实现算法;最后,通过计算机模拟仿真验证了新方法的估计精度更高,性能更好.

为提高工业机器人的工作效率,并延长其寿命,提出一种基于多 目标粒子群算法(MOPSO)的轨迹优化方法.首先采用3-5-3多项式插值的方法,构造关节空间插值轨迹,以时间、能耗和冲击为指标建立目标函数,添加相应的约束条件,然后采用MOPSO求解多目标最优问题,得到Pareto最优解集合.对六自由度PUMA560机器人仿真结果表明:MOPSO算法能够有效地实现轨迹的多目标优化,得到理想均匀的Pareto分布.最后,根据实际工况选择某个解,利用多项式插值得到高阶连续的优化轨迹.

本文针对永磁同步电机,在建立完整的数学模型的基础上,介绍了基于模型预测的永磁电机控制策略.相对传统的PI调节,模型预测控制具有更好的动态响应特性,过度阶段更为平滑.针对低速或者零速状态下的转子角度无感估算,分析了高频注入、滑模观测器和模型参考自适应等算法等不同条件下的估算效果.最后通过仿真对比,证明所设计的模型预测控制系统在转矩响应、动态特性等方面要优于传统的PI调节.

文章主要介绍永磁同步电机的数学模型和矢量控制的基本原理,以空间矢量方法的基木原理为基础,在MATLAB上搭建永磁同步电机矢量控制系统的仿真模型,并对仿真结果进行分析,验证该控制策略的可行性.仿真结果表明:系统构建方法简单,基于矢量控制方法的永磁同步电动机系统的响应速度快,系统运行平稳,验证了该仿真实验平台的有效性.

为了简单高效地对电子元器件进行识别分类,本文提出了一种基于卷积神经网络的电子元器件的识别方法.该方法只需对图像进行简单的预处理,其网络模型能够自动提取图像特征,而且卷积神经网络能减少参数数量,降低计算的复杂度.实验结果表明,该方法无需对图像进行复杂的预处理,其网络模型能自动进行特征提取,能识别多种元器件,精度较高且复杂度较小,能够克服传统图像分类算法的诸多缺点.

现场总线与以太网共同作用于工业现场已成为当今工业控制的新潮流.针对工业现场中存在的总线竞争与共存难题以及当前转换器所存在的实时性和通用性方面的不足,本文提出了一种多类型总线转换器的设计方案.多类型总线转换器选用STM32F107VCT6作为主控芯片,通过移植实时操作系统并采用协议分层转换及中断思想和CRC校验算法,实现了总线协议转换的实时性和数据转发的快速性、精确性.结果表明,本文设计的多类型总线转换器具有良好的实时性且可以快速、准确完成总线协议转换功能、总体运行稳定,已经具备良好的实用性和应用前景.

近年来,随着科技和工业的快速发展,绝对值编码器在其通信技术方面也在逐步地优化与完善,其中SSI协议的输出方式在绝对值编码器领域中应用比较广泛.详细阐述了SSI协议的通信方式,设计出硬件电路,并采用Verilog语言实现了SSI通信协议.通过测试实验,证明了该应用系统抗干扰性强、性能可靠、通信速度快,具有潜在的市场价值.

近年来,光栅编码器的应用领域更加广泛,工业需求逐步增长,精度要求也越来越高.为了满足高速实时采集的要求,本文介绍了一种基于CPLD的光栅编码器采集系统,详细阐述了光栅编码器A、B两路脉冲信号的四倍频细分、相位鉴定以及脉冲计数的方法,并采用Verilog HDL语言编写计数模块程序,在Quartus II平台上对采集脉冲信号进行仿真,充分验证了该设计的可行性与可靠性.仿真结果表明相比于传统设计方法而言,该系统具有高速、稳定可靠、功耗低等优点.

为了保证业务流在交换式工业以太网中传输的实时性,在交换机中引入了优先级调度机制,对源节点的业务流数据进行了流量控制.结合网络演算理论对交换式工业以太网的实时能力进行了分析,计算出交换机对不同数据类型的服务曲线,通过推导出的服务曲线计算出实时数据的最大网络时延和缓冲区大小,对考察交换式工业以太网的服务质量提供了一定的参考价值.

该通信方案以工业手持终端现场应用为背景,针对传统以太网在工业通信中实时性差的问题,提出了一种发送心跳包,建立socket长连接的方法,由此来减少通信过程中频繁建立和关闭连接所消耗的时间.运用XMPP协议实现轻量级、简单实用的消息推送组件,可以进行服务端消息推送从而代替了传统的客户端轮询机制,缩短了响应时间,提高了整个系统的实时性.

为了保证交换式工业以太网中实时数据端到端的传输时延和业务流传输的公平性,避免网络拥塞的出现,在对工业现场业务流类型分析的基础上,提出了一种基于SPQ_WRR队列调度的算法.为了验证该调度算法的有效性,采用了OPNET进行仿真,仿真结果表明,相比于传统的队列调度算法而言,该调度算法有效的保证了实时数据传输的实时性和业务流传输的公平性,同时起到了流量控制的作用,有效的避免了网络拥塞的出现.

This paper was based on the design and implementation of five-axis manipulator, and presented an embedded motion controller based on Cortex-M4 as the kernel of the microprocessor STM32F407. In this design scheme, the communication mode of field bus was introduced, and its high reliability and high performance were used, which makes the motion controller have the characteristics of high openness and modularity. In this paper, the design method of multiple servo motors controlling by CAN bus was provided, which makes the design of the hardware circuit greatly simplified, and the efficiency and reliability of the communication greatly improved. The test shows that the performance of the controller is stable and reliable, and it has practical guidance significance to industrial control field.

In order to achieve the requirement of fast, smooth and accurate speed control of a brushless DC motor, this paper designed an BLDC controller based on Cortex_M3 kernel processor, and implemented hardware and software parts of the control system. The use of real-time operating system FreeRTOS scheduled tasks. Using the speed and current dual PID control algorithm, it formed a double-loop system that BLDC controled in realtime. In order to more effectively reduce the torque ripple, it achieved a 12 sector-free flux observed two or three conduction mode direct torque control. The test results show that the control system has rapid response, wide speed range and high precision, stable and reliable performance, low cost and power consumption, and application prospect is very broad.

随着电子信息技术的不断发展,电子系统模块化的设计思想已经深入人心.因此,加强软件和硬件模块设计经验的相互借鉴意义重大.针对这种情况,借助于有限状态机理论,提出了一种将C程序转化成Verilog HDL描述的具体方法.同时,详细介绍了有限状态机理论,分析了在利用有限状态机进行设计时应该遵循的准则,并给出了一个具体的转化实例和最终的仿真结果.从仿真结果可以看出此方法是可行的.

CANopen protocol is a standard defined by CAN-in-Automation(CiA), and occupies a leading position in the CAN-based industrial sector. In this paper, based on design and implemention of five-axis robot, combined with the widely applications of CANopen protocol in the field of automotive electronics and industrial control, the real-time control of multi-motor system is achieved. CAN bus design method provided herein controlling multiple servo motors, making the hardware design is greatly simplified, and also making the efficiency and reliability of communication increased dramatically. The provided scheme in the actual operation has been fully validated for industrial control applications with practical guidance.

为了提高分布式系统的数据通信性能,采用以太网和RS485总线的集成使用,在不改变原有网络结构的情况下,将RS485总线控制系统改造为以太网分布式控制系统,设计了一种低成本的基于W5100和STC单片机的RS485-以太网协议转换器.在介绍转化器的作用环境基础上,对其硬件结构和软件设计做了简要介绍.经使用证明,设计的转换器可实现RS485和以太网2个网络的透明通信,实现远距离、快速和可靠的数据传输,具有一定的实用性和推广价值.