Human-Robot Collaboration Framework Based on Impedance Control in Robotic Assembly

Human–robot(HR)collaboration(HRC)is an emerging research field because of the complementary advantages of humans and robots.An HRC framework for robotic assembly based on impedance control is proposed in this paper.In the HRC framework,the human is the decision maker,the robot acts as the executor,while the assembly environment provides constraints.The robot is the main executor to perform the assembly action,which has the position control,drag and drop,positive impedance control,and negative impedance control modes.To reveal the characteristics of the HRC framework,the switch condition map of different control modes and the stability analysis of the HR coupled system are discussed.In the end,HRC assembly experiments are conducted,where the HRC assembly task can be accomplished when the assembling tolerance is 0.08 mm or with the interference fit.Experiments show that the HRC assembly has the complementary advantages of humans and robots and is efficient in finishing complex assembly tasks.

Neural Dynamics for Distributed Collaborative Control of Manipulators With Time Delays

Time-delay phenomena extensively exist in practical systems,e.g.,multi-agent systems,bringing negative impacts on their stabilities.This work analyzes a collaborative control problem of redundant manipulators with time delays and proposes a time-delayed and distributed neural dynamics scheme.Under assumptions that the network topology is fixed and connected and the existing maximal time delay is no more than a threshold value,it is proved that all manipulators in the distributed network are able to reach a desired motion.The proposed distributed scheme with time delays considered is converted into a time-variant optimization problem,and a neural dynamics solver is designed to solve it online.Then,the proposed neural dynamics solver is proved to be stable,convergent and robust.Additionally,the allowable threshold value of time delay that ensures the proposed scheme’s stability is calculated.Illustrative examples and comparisons are provided to intuitively prove the validity of the proposed neural dynamics scheme and solver.

Collaborative Simulation Method with Spatiotemporal Synchronization Process Control

When designing a complex mechatronics system, such as high speed trains, it is relatively difficult to effectively simulate the entire system＇s dynamic behaviors because it involves multi-disciplinary subsystems. Currently, a most practical approach for multi-disciplinary simulation is interface based coupling simulation method, but it faces a twofold challenge： spatial and time unsynchronizations among multi-directional coupling simulation of subsystems. A new collaborative simulation method with spatiotemporal synchronization process control is proposed for coupling simulating a given complex mechatronics system across multiple subsystems on different platforms. The method consists of 1） a coupler-based coupling mechanisms to define the interfacing and interaction mechanisms among subsystems, and 2） a simulation process control algorithm to realize the coupling simulation in a spatiotemporal synchronized manner. The test results from a case study show that the proposed method 1） can certainly be used to simulate the sub-systems interactions under different simulation conditions in an engineering system, and 2） effectively supports multi-directional coupling simulation among multi-disciplinary subsystems. This method has been successfully applied in China high speed train design and development processes, demonstrating that it can be applied in a wide range of engineering systems design and simulation with improved efficiency and effectiveness.

Cloud control for IIoT in a cloud-edge environment

The industrial Internet of Things(IIoT)is a new indus-trial idea that combines the latest information and communica-tion technologies with the industrial economy.In this paper,a cloud control structure is designed for IIoT in cloud-edge envi-ronment with three modes of 5G.For 5G based IIoT,the time sensitive network(TSN)service is introduced in transmission network.A 5G logical TSN bridge is designed to transport TSN streams over 5G framework to achieve end-to-end configuration.For a transmission control protocol(TCP)model with nonlinear disturbance,time delay and uncertainties,a robust adaptive fuzzy sliding mode controller(AFSMC)is given with control rule parameters.IIoT workflows are made up of a series of subtasks that are linked by the dependencies between sensor datasets and task flows.IIoT workflow scheduling is a non-deterministic polynomial(NP)-hard problem in cloud-edge environment.An adaptive and non-local-convergent particle swarm optimization(ANCPSO)is designed with nonlinear inertia weight to avoid falling into local optimum,which can reduce the makespan and cost dramatically.Simulation and experiments demonstrate that ANCPSO has better performances than other classical algo-rithms.

Human-Robot Collaborative Planning for Navigation Based on Optimal Control Theory

Navigation modules are capable of driving a robotic platform without direct human participation. However, for some specific contexts, it is preferable to give the control to a human driver. The human driver participation in the robotic control process when the navigation module is running raises the share control issue. This work presents a new approach for two agents collaborative planning using the optimal control theory and the three-layer architecture. In particular, the problem of a human and a navigation module collaborative planning for a trajectory following is analyzed. The collaborative plan executed by the platform is a weighted summation of each agent control signal. As a result, the proposed architecture could be set to work in autonomous mode, in human direct control mode or in any aggregation of these two operating modes. A collaborative obstacle avoidance maneuver is used to validate this approach. The proposed collaborative architecture could be used for smart wheelchairs, telerobotics and unmanned vehicle applications.

Trajectory Planning of High Precision Collaborative Robots

In order to satisfy the high efficiency and high precision of collaborative robots,this work presents a novel trajectory planning method.First,in Cartesian space,a novel velocity look-ahead control algorithm and a cubic polynomial are combined to construct the end-effector trajectory of robots.Then,the joint trajectories can be obtained through the inverse kinematics.In order to improve the smoothness and stability in joint space,the joint trajectories are further adjusted based on the velocity look-ahead control algorithm and quintic B-spline.Finally,the proposed trajectory planning method is tested on a 4-DOF serial collaborative robot.The experimental results indicate that the collaborative robot achieves the high efficiency and high precision,which validates the effectiveness of the proposed method.

Teleoperation strategies research for collaborative welding systems based on virtual reality

Teleoperation control strategies for collaborative welding system which is targeting at giving full play to human’s superiority is designed and the fitness for teleoperation welding task of which are studied. During the teleoperation welding process, 6-DOF controller’s signal can be converted into welding torch’s position, velocity or acceleration changing which is being controlled. For welding purposes, control strategies of four modes are designed, which are static position and posture mode, dynamic position and posture mode, velocity mode and acceleration mode. A test and analysis system for testing the tracking accuracy and reliability of control strategy based on virtual reality is developed. The tracking accuracies of the four control strategies are studied in the following tests with straight line trajectory, curve trajectory or space curve trajectory. The results show that the control strategy in dynamic position and posture mode has best stability and strong adaptability which is the most suitable for the teleoperation system.

An Intelligent Control Method for the Low-Carbon Operation of Energy-Intensive Equipment

Based on an analysis of the operational control behavior of operation experts on energy-intensive equipment,this paper proposes an intelligent control method for low-carbon operation by combining mechanism analysis with deep learning,linking control and optimization with prediction,and integrating decision-making with control.This method,which consists of setpoint control,self-optimized tuning,and tracking control,ensures that the energy consumption per tonne is as low as possible,while remaining within the target range.An intelligent control system for low-carbon operation is developed by adopting the end-edge-cloud collaboration technology of the Industrial Internet.The system is successfully applied to a fused magnesium furnace and achieves remarkable results in reducing carbon emissions.

Design of Multi-domain Collaborative Simulation System for Dual Clutch Transmission Based on CAN Bus

A multi-domain collaborative simulation(MDCS) system for dual clutch transmission(DCT) was presented based on controller area network(CAN) bus.An interface card of CAN bus was designed,in which MDCS subsystems were linked as the nodes according to the interface mode of MDCS.A DCT simulation model was established based on Matlab/Simdriveline,whose running process was accurately controlled by the designed control system.The playback system of vehicle state(VPS) was proposed whose input was the road-test data,with a real vehicle test environment for the development of transmission control unit(TCU) being provided.A DCT kinematic system model was set up,and the running status of DCT parts could be displayed in real time.The functions of MDCS were verified based on the extra-urban driving cycle(EUDC) and the vehicle road-test data respectively.The results show the functions of MDCS are accomplished,and the unified supporting platform for the development of TCU is achieved by MDCS.

A Temporal Multi-Tenant RBAC Model for Collaborative Cloud Services

Multi-tenant collaboration brings the challenge to access control in cloud computing environment.Based on the multi-tenant role-based access control(MT-RBAC)model,a Temporal MT-RBAC(TMT-RBAC)model for collaborative cloud services is proposed.It adds the time constraint between trusted tenants,including usable role time constraint based on both calendar and interval time.Analysis shows that the new model strengthens the presentation ability of MT-RBAC model,achieves the finer-grained access control,reduces the management costs and enhances the security of multi-tenant collaboration in cloud computing environment.

Multi-telerobot collaboration based on coordinated controller

A coordinated controller used for multi-telerobots collaboration was presented based on the strategy of shared control. First, it can overcome the effect of time delay. And, it combines the intelligence of the master side and the slave side, which cannot only increase the efficiency and the safety of the system but also relieve the burden and requirements of the operator. The controller can also cope with the collision between two telerobots. A simulation experiment was carried out to verify the validity of the controller for two slave robots.

Multimodal collaborative BCI system based on the improved CSP feature extraction algorithm

Background As a novel approach for people to directly communicate with an external device,the study of brain-computer interfaces(BCIs)has become well-rounded.However,similar to the real-world scenario,where individuals are expected to work in groups,the BCI systems should be able to replicate group attributes.Methods We proposed a 4-order cumulants feature extraction method(CUM4-CSP)based on the common spatial patterns(CSP)algorithm.Simulation experiments conducted using motion visual evoked potentials(mVEP)EEG data verified the robustness of the proposed algorithm.In addition,to freely choose paradigms,we adopted the mVEP and steady-state visual evoked potential(SSVEP)paradigms and designed a multimodal collaborative BCI system based on the proposed CUM4-CSP algorithm.The feasibility of the proposed multimodal collaborative system framework was demonstrated using a multiplayer game controlling system that simultaneously facilitates the coordination and competitive control of two users on external devices.To verify the robustness of the proposed scheme,we recruited 30 subjects to conduct online game control experiments,and the results were statistically analyzed.Results The simulation results prove that the proposed CUM4-CSP algorithm has good noise immunity.The online experimental results indicate that the subjects could reliably perform the game confrontation operation with the selected BCI paradigm.Conclusions The proposed CUM4-CSP algorithm can effectively extract features from EEG data in a noisy environment.Additionally,the proposed scheme may provide a new solution for EEG-based group BCI research.

智能采煤机器人关键技术

采煤机是综采工作面的核心装备,研发智能采煤机器人是实现综采工作面智能化的关键。综合分析当前采煤机机器人化研究进程中的传感检测、位姿控制、速度控制、截割轨迹规划与跟踪控制等技术的研究现状,提出研发智能采煤机器人必须破解的“智能感知、位姿控制、速度控制、截割轨迹规划与跟踪控制、位-姿-速协同控制”五大关键技术,并给出解决方案。针对智能感知问题,提出了构建智能感知系统思路,给出了智能采煤机器人智能感知系统的架构,实现对运行状态、位姿、环境等全面感知,为智能采煤机器人安全、可靠运行提供保障;针对位姿控制问题,提出了智能PID位姿控制思路,给出了改进遗传算法的PID位姿控制方法,实现了智能采煤机器人位姿精准控制;针对速度控制问题,提出了融合“力-电”异构数据的截割载荷测量思路,给出了基于神经网络算法的截割载荷测量方法,实现了截割载荷的精准测量;提出牵引与截割速度自适应控制思路,给出了人工智能算法牵引与截割速度决策方法和滑模自抗扰控制的牵引与截割速度控制方法,实现了智能采煤机器人速度精准自适应控制;针对截割轨迹规划与跟踪控制问题,提出了截割轨迹精准规划思路,给出了融合地质数据和历史截割数据的截割轨迹规划模型,实现了截割轨迹的精准规划;提出了截割轨迹精准跟踪控制思路,给出了智能插补算法的截割轨迹跟踪控制方法,实现了智能采煤机器人截割轨迹高精度规划与精准跟踪控制;针对“位-姿-速”协同控制问题,提出了“位-姿-速”协同控制参数智能优化思路,给出了基于多系统互约束的改进粒子群“位-姿-速”协同控制参数优化方法,实现了智能采煤机器人智能高效作业。深入研究五大关键技术破解思路,有利于加快推动研发高性能、高效率、高可靠的智能采煤机器人。

煤矿智能快速掘进关键技术研究现状及展望

针对煤矿巷道掘进智能化建设情况,探讨了现阶段分别以连采机、掘锚一体机、全断面掘进系统、掘锚机为核心的四大类智能快速掘进成套装备发展现状,分析了四大类智能快掘装备与地质条件适用性,提出了实现煤矿智能化掘进需要解决的关键技术的问题,探讨了以信息传输与智能分析技术、智能感知技术、精确定位导航技术,自主定型定向截割技术、掘进机远程自主截割控制技术以及多级多工序智能协同控制技术为基础的智能化掘进实现途径;基于复杂地质条件下煤矿巷道掘进亟待解决的关键问题,提出了以掘进作业功能需求、掘进工艺要求为依据的系统化分析、模块化设计、功能优化组合的设计方法;研究了以虚控实、虚实结合的多级数字孪生构架,基于掘进巷道设备、环境、地质构造多维信息再现实现掘进机远程控制;提出了单机智能化、系统协同化、井下智控与地面远程监控相协同的控制方法。开发了新型的无重复碾压柔性超前支护技术、截割部多级伸缩截割技术、智能锚固机组多钻机并行作业等技术,研制了具有掘、支、锚、运、探多工序并行作业的新型快速掘进作业联合机组,提出了掘进机器人、超前支护机器人、锚固机器人、辅助运输机器人组柔性并行作业技术;提出了基于数据驱动的多机多工序协同控制行为规划决策方法。提出构建完整的煤矿井下跨系统全时空信息数字感知体系,构建集井下现场生产状态、掘进巷道空间信息、掘进装备状态、风险信息等多参量、多尺度、全时空特性的数据感知智能化监控平台,实现虚拟系统与实际掘进系统实时通信,通过数据驱动规划分析实现智能化、少人化掘进。

面向复杂工况的液力变矩器与变速箱效能优化协同控制策略

针对工程机械在复杂工况下能源利用率不高的问题,提出了一种液力变矩器与变速箱效能优化协同控制策略。首先,在装载机功率与力学平衡的基础上,构造了基于牵引性能理论的装载机动力传动系统仿真平台,并通过装载机循环工况采集到的实验数据验证了其有效性和可靠性;其次,基于发动机与液力变矩器台架实验,研究了ZL50型装载机的牵引特性,对比了其在起步、举升、铲掘、匀速4种不同牵引阶段的动力性能,分析了液力变矩器的闭锁点对装载机动力性、平顺性和经济性的影响;最后,提出了面向复杂工况的液力变矩器与变速箱效能优化协同控制策略,并对优化前后的装载机效能进行了对比分析。研究结果表明:在相同的V型循环工况下,采用所提出的控制策略,装载机等油耗输出能量从372.69 kW·h·mL^(-1)提高到420.51 kW·h·mL^(-1),整机效能提高了约12.8%。所提策略可为大型工程机械传动效率低、燃料消耗大、污染排放严重等问题提供解决方案。

基于直流电压动态修正的柔性多状态开关自适应下垂控制

为了满足配电网的多种互联需求,柔性多状态开关(flexible multi-state switch,FMSS)已衍生出多种互联应用的技术形态,多端FMSS与双端FMSS相比更具经济性和可靠性,已成为研究热点。传统下垂控制通过改变直流侧电压实现不平衡功率的消纳,但直流侧电压的偏离会影响系统安全可靠运行。针对模块化多电平换流器(modular multilevel converter,MMC)的多端FMSS系统,提出了一种改进型下垂控制策略,根据换流器消纳的有功功率实时动态改变直流电压的参考值和下垂增益,实现了直流电压的无偏差运行,既能避免换流站过载,又能解决不平衡功率消纳引起的电压偏离问题,提高了系统的稳定性。另外,由于MMC自身结构特性和PI参数整定困难,将传统的电流内环改为模型预测控制,并采用典型的二阶Runge-Kutta法对状态方程进行离散化,提高了控制精度。最后基于MATLAB/Simulink仿真软件搭建了四端FMSS系统模型,验证了所提控制策略的可行性与有效性。

煤矿防冲钻孔机器人全自主钻进系统关键技术

针对高地应力矿井钻孔卸压作业智能化程度低的技术难题,总结分析了国内外钻孔卸压技术和装备的研究现状,指出研发高性能、高可靠、高效率的防冲钻孔机器人全自主钻进系统是破解冲击地压防治难题的重要发展方向。为此,凝练了影响钻进系统性能的“孔位精准识别、钻具姿态精确感知、无线电磁随钻智能检测、钻具运行状态智能识别和钻进系统精确控制”五大关键技术,并给出了解决思路和方法。针对在复杂恶劣环境下卸压孔的精确识别问题,设计了融合图像尺寸调节和多阶段训练模式的卸压孔图像样本扩充SinGAN模型,引入多层特征融合优化的FasterRCNN,构建了基于改进SqueezeNet轻量级网络架构的孔位识别模型,以实现卸压孔位的准确快速识别;针对钻具姿态精确感知问题,提出了基于改进梯度下降法算法优化无迹卡尔曼滤波的惯性测量单元(Inertial Measurement Unit,IMU)初始对准方法,设计了多个IMU的空间阵列布局方式,研究了基于BP神经网络的钻具姿态误差补偿方法,旨在提高钻具姿态的解算精度,实现精准钻孔卸压;针对复杂地质环境下钻进工况的精确检测问题,搭建了煤矿井下随钻测量无线电磁传输系统架构,探讨了微弱电磁波信号自适应调制和随钻高速双向电磁传输技术原理,研究了孔底地质参数、几何参数和工程参数的测量原理和实现过程;针对钻进系统运行状态识别问题,构建了钻进信号时域、频域、时频域的多域特征和深度网络高级特征提取架构,提出了钻进系统关键零部件健康状态评估和故障诊断技术,构建了基于改进蝙蝠优化长短期记忆网络的卡钻风险因子预测模型,实现对卸压钻具卡钻状态的准确预测;针对钻进系统的精确控制问题,分析了钻进系统的液压系统工作原理,构建了考虑煤岩性状的钻进系统精确控制方案,探讨了基于转矩和位置的钻进系统最优控制参数求解原理,旨在实现钻进回转系统和给进系统的智能协同控制和并行作业。

油田开发中精细油藏描述成果平台建设研究

精细油藏描述是油田开发最基础的工作之一,历来受到研究者的高度重视。目前精细油藏描述中存在的突出问题主要包括研究成果继承性差、基础资料存储不规范、专业软件需求缺口大、成果应用需加强和成果存储管理不规范等5方面。文章通过精细油藏描述成果平台建设,可以从基础数据的整理准备、专业软件共享和协同研究、成果标准规范化存储管理等方面解决上述问题。精细油藏描述数据管理主要包括项目整体数据信息的统计和分析、项目研究数据的整理和统计、成果平台与其他数据平台的对接和数据调用等。精细油藏描述协同研究过程主要包括专业软件的平台实现和使用、不同专业软件之间中间成果的转换和调用、研究工作的自动化实现和完成。精细油藏描述成果存储和管理主要包括成果上传管理中格式的统一规范、成果存储上传中的质量控制、成果生产应用中的跟踪和更新。

基于产教融合的材料专业课程体系改革研究

高等教育肩负创新型人才培养重要使命,对支撑科技发展和行业转型升级起到输送人才的关键作用。吉林大学材料成型及控制专业课程体系以产教融合育人为改革目标,针对产业与教学脱节、培养模式固化单一、育人软硬件支撑条件不足等问题,从教学实践课程体系顶层设计优化、科学素养与工程能力双驱动发展和多元育人平台建设等方面,结合吉林省汽车制造与轨道交通支柱产业集群优势,进行具有产教融合特色的课程体系改革研究,探索创新型人才培养新范式,实现“教学支撑科技,科技反哺教学”双驱动的多元协同育人新生态。

船舶远程驾驶人机主从博弈控制方法研究

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