Neural Dynamics for Cooperative Motion Control of Omnidirectional Mobile Manipulators in the Presence of Noises: A Distributed Approach

This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning(CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming(QP) and solved online utilizing a noise-tolerant zeroing neural network(NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.

A novel intrusion detection model for the CAN bus packet of in-vehicle network based on attention mechanism and autoencoder

The attacks on in-vehicle Controller Area Network(CAN)bus messages severely disrupt normal communication between vehicles.Therefore,researches on intrusion detection models for CAN have positive business value for vehicle security,and the intrusion detection technology for CAN bus messages can effectively protect the invehicle network from unlawful attacks.Previous machine learning-based models are unable to effectively identify intrusive abnormal messages due to their inherent shortcomings.Hence,to address the shortcomings of the previous machine learning-based intrusion detection technique,we propose a novel method using Attention Mechanism and AutoEncoder for Intrusion Detection(AMAEID).The AMAEID model first converts the raw hexadecimal message data into binary format to obtain better input.Then the AMAEID model encodes and decodes the binary message data using a multi-layer denoising autoencoder model to obtain a hidden feature representation that can represent the potential features behind the message data at a deeper level.Finally,the AMAEID model uses the attention mechanism and the fully connected layer network to infer whether the message is an abnormal message or not.The experimental results with three evaluation metrics on a real in-vehicle CAN bus message dataset outperform some traditional machine learning algorithms,demonstrating the effectiveness of the AMAEID model.

Co-design for an SoC embedded network controller

With the development of Ethernet systems and the growing capacity of modem silicon technology, embedded communication networks are playing an increasingly important role in embedded and safety critical systems. Hardware/software co-design is a methodology for solving design problems in processor based embedded systems. In this work, we implemented a new 1-cycle pipeline microprocessor and a fast Ethemet transceiver and established a low cost, high performance embedded network controller, and designed a TCP/IP stack to access the Intemet. We discussed the hardware/software architecture in the forepart, and then the whole system-on-a-chip on Altera Stratix EP1S25F780C6 device. Using the FPGA environment and SmartBit tester, we tested the system＇s throughput. Our simulation results showed that the maximum throughput of Ethemet packets is up to 7 Mbps, that of UDP packets is up to 5.8 Mbps, and that of TCP packets is up to 3.4 Mbps, which showed that this embedded system can easily transmit basic voice and video signals through Ethemet, and that using only one chip can realize that many electronic devices access to the Intemet directly and get high performance.

M/S Controller Area Network(CAN) System Using Shared-Clock Scheduler

The Controller Area Network (CAN) is a well established control network for automotive and automation control applications. Time-Triggered Controller Area Network (TTCAN) is a recent development which introduces a session layer,for message scheduling,to the existing CAN standard,which is a two layer standard comprising of a physical layer and a data link layer. TTCAN facilitates network communication in a time-triggered fashion,by introducing a Time Division Multiple Access style communication scheme. This allows deterministic network behavior,where maximum message latency times can be quantified and guaranteed. In order to solve the problem of determinate time latency and synchronization among several districted units in one auto panel CAN systems,this paper proposed a prototype design implementation for a shared-clock scheduler based on PIC18F458 MCU. This leads to improved CAN system performance and avoid the latency jitters and guarantee a deterministic communication pattern on the bus. The real runtime performance is satisfied.

Design of Motion Controller Based on Touch Screen

Motion controller plays a dominant role in motion control system. With the progress and improvement of motion control technology, the research and application of open, high-performance, low-cost and universal embedded motion controller becomes the necessity of the market. The major objective of the paper is to establish the basic software and hardware platform of a high-performance, low-cost and universal embedded motion controller and study the application. And the paper proposes the idea of developing a low-cost and economic touchscreen motion controller, which provides valuable reference for the relevant research and development in China.

基于巡检移动机器人运动控制的CAN总线通信技术研究

在现代工业应用中,巡检移动机器人凭借其自动化和智能化的特点,已广泛应用于设备监控与维护领域。这些机器人的有效运作依赖于高效的控制系统和可靠的通信技术。其中,控制器局域网(Controller Area Network,CAN)总线技术因其高可靠性和实时性,在机器人通信系统中占据重要地位。文章详细分析巡检机器人的运动控制需求,并基于这些需求设计针对性的CAN总线通信方案,包括网络结构、数据帧格式以及通信协议和错误处理机制。

LESO-based Position Synchronization Control for Networked Multi-Axis Servo Systems With Time-Varying Delay

The position synchronization control(PSC) problem is studied for networked multi-axis servo systems(NMASSs) with time-varying delay that is smaller than one sampling period. To improve the control performance of the system, time-varying delays, modeling uncertainties, and external disturbances are first modeled as a lumped disturbance. Then, a linear extended state observer(LESO) is devised to estimate the system state and the lumped disturbance, and a linear feedback controller with disturbance compensation is designed to perform individual-axis tracking control. After that, a cross-coupled control approach is used to further improve synchronization performance. The bounded-input-bounded-output(BIBO) stability of the closedloop control system is analyzed. Finally, both simulation and experiment are carried out to demonstrate the effectiveness of the proposed method.

A Multi-Interface Remote Monitoring and Control System Architecture Based on Embedded Server

This paper presents a multi-interface embedded server architecture for remote real-time monitoring system and distributed monitoring applications. In the scheme,an embedded microprocessor( LPC3250 from NXP) is chosen as the CPU of the embedded server with a linux operation system( OS) environment. The embedded server provides multiple interfaces for supporting various application scenarios. The whole network is based on local area network and adopts the Browser / Server( B / S) model. The monitoring and control node is as a browser endpoint and the remote node with an embedded server is as a server endpoint. Users can easily acquire various sensors information through writing Internet protocol address of remote node on the computer browser. Compared with client / server( C / S) mode,B / S model needs less maintain and can be applicable to large user group. In addition,a simple network management protocol( SNMP) is used for management of devices in Internet protocol( IP) networks. The results of the demonstration experiment show that the proposed system gives good support to manage the network from different user terminals and allows the users to better interact with the ambient environment.

Robust Adaptive Neural Network Control for XY Table

This paper proposed a robust adaptive neural network control for an XY table. The XY table composes of two AC servo drives controlled independently. The neural network with radial basis function is employed for velocity and position tracking control of AC servo drives to improve the system’s dynamic performance and precision. A robust adaptive term is applied to overcome the external disturbances. The stability and the convergence of the system are proved by Lyapunov theory. The proposed controller is implemented in a DSP-based motion board. The validity and robustness of the controller are verified through experimental results.

Design of motion control system of pipeline detection AUV

A great number of pipelines in China are in unsatisfactory condition and faced with problems of corrosion and cracking,but there are very few approaches for underwater pipeline detection.Pipeline detection autonomous underwater vehicle(PDAUV) is hereby designed to solve these problems when working with advanced optical,acoustical and electrical sensors for underwater pipeline detection.PDAUV is a test bed that not only examines the logical rationality of the program,effectiveness of the hardware architecture,accuracy of the software interface protocol as well as the reliability and stability of the control system but also verifies the effectiveness of the control system in tank experiments and sea trials.The motion control system of PDAUV,including both the hardware and software architectures,is introduced in this work.The software module and information flow of the motion control system of PDAUV and a novel neural network-based control(NNC) are also covered.Besides,a real-time identification method based on neural network is used to realize system identification.The tank experiments and sea trials are carried out to verify the feasibility and capability of PDAUV control system to complete underwater pipeline detection task.

Control system design of hybrid fuel cell city bus

This paper introduced the design of the hybrid powertrain of the Fuel Cell City Bus demonstrated in 2008 Beijing Olympic Games. The configuration of the hybrid fuel cell powertrain was introduced. The safety of hydrogen storage and delivery system, the hydrogen leakage alarm system were developed. The real-time distributed control and diagnosis system based on the Time Trigger Controller Area Network （TTCAN） with 10 ms basic control period was developed. The concept and implementation of processor （or controller） monitor and process （or task） monitor technique based on the TYCAN were applied in this paper. The fault tolerant control algorithm of the fuel cell engine and the battery man- agement system were considered. The demonstration experience verified that the fault tolerant control was very important for the fuel cell city bus.

Research of network technology for Intelligent Circuit Breaker Controller

With the current development trend of Ethernet gradually towards the control network of plant-floor layer and devices layer, much management information on Intelligent Circuit Breaker Controller (ICBC) is becoming distributed and networked. This paper describes a mixing structure of complex industrial field control network based on Ethernet frame, then mainly discusses three network management methods of ICBC, such as the interconnection method based on PCI, embedded gateway and em- bedded Web server. At the same time, it also gives the basic hardware framework of implementing interconnection, the type of main components, and the real-time operation system supporting the embedded TCP/IP protocols and Web server.

Adaptive neural network control for coordinated motion of a dual-arm space robot system with uncertain parameters

Control of coordinated motion between the base attitude and the arm joints of a free-floating dual-arm space robot with uncertain parameters is discussed. By combining the relation of system linear momentum conversation with the Lagrangian approach, the dynamic equation of a robot is established. Based on the above results, the free-floating dual-arm space robot system is modeled with RBF neural networks, the GL matrix and its product operator. With all uncertain inertial system parameters, an adaptive RBF neural network control scheme is developed for coordinated motion between the base attitude and the arm joints. The proposed scheme does not need linear parameterization of the dynamic equation of the system and any accurate prior-knowledge of the actual inertial parameters. Also it does not need to train the neural network offline so that it would present real-time and online applications. A planar free-floating dual-arm space robot is simulated to show feasibility of the proposed scheme.

MULTITASK SCHEDULING IN NETWORKED CONTROL SYSTEMS WITH APPLICATION TO LARGE SCALE VEHICLE CONTROL

Aiming at scheduling problems of networked control system （NCS） used to fulfill motion synthesis and cooperation control of the distributed multi-mechatronic systems, the differences of network scheduling and task scheduling are compared, and the mathematic description of task scheduling is presented. A performance index function of task scheduling of NCS according to task balance and traffic load matching principles is defined. According to this index, a static scheduling method is designed and implemented to controlling task set simulation of the DCY100 transportation vehicle. The simulation results are applied successfully to practical engineering in this case so as to validate the effectiveness of the proposed performance index and scheduling algorithm.

The Design and Realization of Network Remote Control Based on Embedded Systems

In order to achieve remote control problems for the intelligent home appliances, The paper presents a realization method through the Internet and GSM remote to control appliances of smart home, and given circuit. And described in detail the hardware and software design of smart home appliances and their control method. Test results show that the system is stable and reliable.

西门子SIMOTION运动控制器在网络诊断方面的应用

本文介绍了西门子SIMOTION运动控制器在整机设备中的使用,以及其作为核心控制器,在整机设备中网络诊断功能的实现和应用。着重介绍了西门子SIMOTION运动控制器设计和编程,以及西门子SCOUT软件设置的具体方案和实施步骤。经实际检验,其完全满足设计要求及实际需求。

基于嵌入式技术的运动目标控制与自动追踪系统设计

针对目前移动机器人运动目标定位不准确和追踪过程中容易丢失的问题,设计了一种基于嵌入式技术的运动目标控制与自动追踪系统。本系统以光斑模拟运动目标,通过算法编程不但可以实现目标的运动轨迹控制,还可对其运动轨迹进行自动追踪。本设计以嵌入式芯片STM32F103为核心,通过OpenMV进行图像数据处理,并由PID精确算法调节舵机,从而控制光斑在屏幕上按照设定程序进行移动和追踪。经测试,该系统能够准确地完成运动目标的控制和自动追踪任务,反应灵敏,性价比高,可广泛应用于运动目标追踪等智能控制设备中。

小型无人有缆遥控水下机器人智能控制方法

针对深度确定性策略梯度(DDPG)算法应用于无人有缆遥控水下机器人(ROV)运动控制时存在的坏样本影响学习稳定性、缺少环境探索能力以及学习时间长难收敛等问题,从神经网络结构、噪声引入和融合监督学习3个方面对DDPG算法进行改进,并提出了基于混合神经网络结构和参数噪声的监督式DDPG算法。仿真结果表明,监督式DDPG算法比常规DDPG算法和传统比例-积分-微分(PID)算法更加有效。

基于人工智能技术的机器人运动控制系统设计

设计一种基于人工智能技术的机器人运动控制系统,确保机器人更好地理解人类的意图,并提供更加人性化的服务。该系统通过运动数据采集与传输组件连接机器人的轴电机,采集机器人当前运动数据后,将其传输到控制器组件内,控制器组件依托X86架构工控机,使用PIC总线将采集到的机器人当前运动数据发送到基于人工智能技术的机器人运动路径规划模块内。该模块运用人工智能技术中的A*算法获取机器人轨迹路径规划结果后,依据该路径规划结果,将人工智能技术中的神经网络和模糊B样条基函数相结合,建立模糊B样条基函数神经网络控制器。该控制器输出机器人运动控制指令,并发送给伺服驱动器组件,伺服驱动器负责驱动机器人轴电机,控制机器人运动。实验结果表明:所设计系统具备较强的机器人路径规划能力,可在复杂路径情况下实现机器人运动控制,且控制精度和控制阶跃响应能力均较强。

现代运动控制教学实训设备的设计与实现

电机控制是现代电气自动化技术专业学生须掌握的技能,也是培养学生工程实践能力的主要途径。目前运动控制实训教学设备中仍大多以继电器—接触器控制和PLC控制继电器方式为主。随着工业互联网、人工智能、工业大数据的发展,采用工业网络通信控制电机的方式应用越来越多,通过网络通信控制电机的方式无复杂的控制接线,搭建的系统具有极高的灵活性,适应现在电机控制的发展需求。为此,本项目在传统教学设备的基础上,集成工业网络控制、PLC和继电器-接触器控制电机的方式,完成现代运动控制教学实训设备的设计。