圆环面上纤维轨迹的计算机辅助设计

曲面上的曲线造型是计算机图形领域的一个新的研究热点,而且它们在纤维织物编织,三维服装裁剪以及复合材料的纤维缠绕轨迹设计等领域有十分广泛的应用,为了解决圆环面上纤维轨迹的计算机辅助设计问题,研究了圆环面上测地线的解析解以及拟测地线数值求解的具体算法并给出了其表达式,测地线是曲面上两点之间最短距离的曲线段,在一般曲面上没有解析解,但是在圆环面上却可求出其精确的解析解,但在曲面的边沿部分,测地线因不能实现自然的折返过渡,于是拟测地线就被引进到曲面上的曲线造型设计之中,在拟测地线分析研究基础上,给出了圆环面上拟测地线的方程及数值解法,通过其在一个实例中的应用结果证明,该方法可获得织物的纺织条纹以及缠绕物体的纤维轨迹。     

三轴纤维缠绕机自动控制系统的设计

根据纤维缠绕原理,分析了微机控制系统的组成、结构、功能及其软硬件的设计,并给出了控制参数的数学描述,叙述了系统的工作原理.     

纤维缠绕机的计算机控制系统设计

从纤维缠绕机的结构和工作原理出发,介绍了纤维缠绕机的控制系统。提出了以计算机为核心的控制系统的硬件组成,并给出了控制程序的设计与运行结果。该控制系统使得缠绕机缠绕工艺有很大的提高。     

用于弯管的计算机辅助纤维缠绕

纤维缠绕模式在计算机辅助纤维缠绕中起着关键的作用,然而对于非轴对称纤维缠绕设计,目前还没有稳定、可靠的模式设计方法.另外,如何有效地处理纤维路径设计中产生的大量数据也是非轴对称纤维缠绕的一大难题.给出了用于弯管的纤维缠绕模式和一种被称为节点存储法的新的数据处理方法.     

A Simple Robotic System for Neurorehabilitation

In the recent past, several researchers have shown that important variables in relearning motor skills and in changing the underlying neural architecture after stroke are the quantity, duration, content, and intensity of training sessions. Unfortunately, when traditional therapy is provided in a hospital or rehabilitation center, the patient is usually seen for few hours a week. Robot-mediated therapies could improve this situation but even if interesting results have been achieved by several groups, the use of robot-mediated therapy has not become very common in clinical practice. This is due to many different reasons (e.g., the “technophobia” of some clinicians, the need for more extensive clinical trials) but one of the more important is the cost and the complexity of these devices which make them difficult to be purchased and used in all the clinical centers. The aim of this work was to verify the possibility of improving motor recovery of hemiparetic subjects by using a simple mechatronic system. To achieve this goal, our system (named “MEchatronic system for MOtor recovery after Stroke” (MEMOS)) has been designed with the aim of using mainly “off-the-shelf products” with only few parts simply manufactured with standard technology, when commercial parts were not available. Moreover, the prototype has been developed taking into account the requirements related to the clinical applicability such as robustness and safety. The MEMOSsystem has been used during clinical trials with subjects affected by chronic hemiparesis (<6 months from the cerebrovascular accident). The results obtained during these experiments seem to showthat notwithstanding the simple mechatronic structure characterizing theMEMOSsystem, it is able to help chronic hemiparetics to reduce their level of impairment. Further clinical experiments with acute and chronic subjects will be carried out in order to confirm these preliminary findings. Moreover, experiments for tele-rehabilitation of patients will be also carried out. Silvestro Micera was born in Taranto, Italy, on August 31, 1972. He received the University degree (Laurea) in electrical engineering from the University of Pisa, Pisa, Italy, in 1996, and the Ph.D. degree in biomedical engineering from the Scuola Superiore Sant'Anna, Pisa, Italy, in 2000. From 1998 to 2001, he was the Project Manager of the EU GRIP Project (ESPRIT LTR Project 26322, “An integrated system for the neuroelectrIic control of grasp in disabled persons”). During 1999, he was a Visiting Researcher at the Center for Sensory-Motor Interaction, Aalborg University. Since May 2000, he has been an Assistant Professor of Biomechanical Engineering at the Scuola Superiore Sant'Anna. He is currently involved in several projects on neuro-robotics and rehabilitation engineering. His research interests include the development of neuro-robotic systems (interfacing the central and peripheral nervous system with robotic artefacts) and the development of mechatronic and robotic systems for function restoration in disabled persons. Dr. Micera is an Associate Editor of the IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING and member of the IEEE Engineering in Medicine and Biology and Robotics and Automation Societies. M. Chiara Carrozza received the Laurea degree in physics from the University of Pisa, Pisa, Italy, in 1990. Since 2001, she has been an Associate Professor of biomedical robotics at the Scuola Superiore Sant'Anna, Pisa, Italy. She is the co-cordinator of the Advanced Robotics Technology and Systems Laboratory where she is responsible for some national and international projects in the fields of biorobotics. Her research interests are in the fields of biorobotics (artificial hands, upper limb exoskeletons), rehabilitation engineering (neurorehabilitation, domotic, and robotic aids), and biomedical microengineering (microsensors, tactile sensors). She is an author of several scientific papers and international patents. Eugenio Guglielmelli received the Laurea degree and the PhD in electronics engineering from the University of Pisa, Italy, in 1991 and in 1995, respectively. He is currently Associate Professor of Bioengineering at Campus Bio-Medico University in Rome, Italy, where he teaches the courses of Bio-Mechatronics and of Rehabilitation Bioengineering, and where he also recently co-founded the new Research Laboratory of Biomedical Robotics & Electro-Magnetic Compatibility. He has been working in the field of biomedical robotics over the last fifteen years at Scuola Superiore Sant'Anna where he also served from 2002 to 2004 as the Head of the Advanced Robotics Technology & Systems Laboratory (ARTS Lab), founded by prof. Paolo Dario in 1991. His main current research interests are in the fields of novel theoretical and experimental approaches to human-centered robotics and to biomporphic control of mechatronic systems, and in their application to robot-mediated motor therapy, assistive robotics, neuro-robotics and neuro-developmental engineering. He serves in the Editorial Board of the International Journal on Applied Bionics and Biomechanics. He has been Guest Co-Editor of the Special Issue on Rehabilitation Robotics of the International Journal ‘Autonomous Robots’. He is member of the IEEE Robotics & Automation Society, of the IEEE Engineering in Medicine & Biology Society, of the Society for Neuroscience, and of the Association for the Advancement of Assistive Technology in Europe (AAATE). He served (2002–03) as the Secretary of the IEEE Robotics & Automation Society (RAS) and he is currently Co-chair of the RAS Technical Committee on Rehabilitation Robotics. He serves in the Programme Committees of several International Conferences, such as ICRA, IROS, ICAR, AIM, BIOROB and others. He was/is a member of the Organizing Committees of ICAR2003, IROS2004, IFAC/SYROCO2006 and ICRA2007. Giovanni Cappiello received the M.E. degree from the University of Pisa, Pisa, Italy. He is currently working towards the Ph.D. degree in robotics at the ARTS Lab of the Scuola Superiore Sant'Anna Pisa. He worked on the RTR IV Prosthetic Hand Project. Among his research interests are rehabilitation technologies, biomedical and surgical devices, osseointegration, and biomimetic artificial sensors. He is involved in the design of antropomorphic hands and arm and in the exploitation of compliant joints. Franco Zaccone was born in Policoro, Italy. He received the University degree (Laurea) in electrical engineering from the University of Pisa, Pisa, Italy, in 2000. Since June 2000, he has been a Research Assistant at the Advanced Robotics Technologies and Systems Laboratory, Scuola Superiore Sant'Anna, Pisa. His research interests include the design of hardware systems for rehabilitation engineering and motion analysis. Cinzia Freschi was born in Caserta, Italy, on December 25, 1969. She received the University degree (Laurea) in computer engineering from the University of Pisa, Pisa, Italy, in 1998. Since 1998, she has been research assistant at the Advanced Robotics Technology and Systems Laboratory (ARTSLAB), Scuola Superiore Sant'Anna. Her research interests are in the filed of rehabilitation engineering and neuro-robotics. Roberto Colombo received the Dr. Eng. degree in electrical engineering from the Politecnico of Milano, Milan, Italy, in 1980. Since 1981, he has been a Research Engineer in the Bioengineering Department of the “Salvatore Maugeri” Foundation, IRCCS, Rehabilitation Institute, Veruno, Italy. From 1998 to 2001, he was a Partner of the European Community project “Prevention of muscular disorders in operation of computer input devices (PROCID).” From 2001 to 2004, he was the Coordinator of the project “Tecniche robotizzate per la valutazione ed il trattamento riabilitativo delle disabilitá motorie dell'arto superiore,” 2001-175, funded by the Italian Ministry of Health. His research interests include robot-aided neurorehabilitation, muscle tone and spasticity evaluation, muscle force and fatigue assessment, speech production mechanisms study, cardiovascular control assessment by spectral analysis of heart rate variability signals, and respiratory mechanics assessment. He has taught several national courses in the field of neurorehabilitation. He is the author of over 20 papers and the co-editor of one book on the subject of speech production mechanisms. Alessandra Mazzone received the degree (Diploma) in computer science, from the ITIS “Leonardo da Vinci,” Borgomanero, Italy, in 1988. Since 1989, she has been a Programmer at the Bioengineering Department, the Fondazione Salvatore Maugeri, Rehabilitation Institute of Veruno (NO), Italy. Her research interests include robot-aided neurorehabilitation, cardiovascular control assessment by spectral analysis of heart rate variability signals, and respiratory mechanics assessment. Carmen Delconte received the Diploma in neurophysiology techniques from the University of Pavia, Pavia, Italy, in 1989. She is currently with the Clinical Neurophysiology Unit, Scientific Institute of Veruno “Salvatore Maugeri” Foundation, Rehabilitation Institute, Veruno, Italy. Her research concerns the quantification of muscle tone, emg-biomechanical studies, and the robotic rehabilitation of upper limb in cerebrovascular diseases. She has been published in the clinical and electrophisiological field of neuromuscular diseases and on the topic of stroke patients rehabilitation. Her current research is focused on the evaluation and treatment of upper limbs disorders like spasticity and paresis. Dr. Delconte is a member of the Italian Neurophysiology Technician Society. Fabrizio Pisano received the M.D. degree from the University of Milan, Milan, Italy, in 1981. In 1986, he completed his training as resident in neurology and became Neurologist at the same University He was a teacher in “Electromyography” from 1991 to 1997 at the School of Physical Medicine and Rehabilitation, the University of Turin, Torino, Italy. He has taught several national and international electromyographic courses on hand neuromotor rehabilitation, occupational pathology, rehabilitation therapy, muscle fatigue, posture and movement, clinical neurophysiology, and EMG Culture. He was a Scientific Project co-leader of a telethon program (1994–1996); speech motor control in ALS; a search for an early marker of disease. He was the Project Leader of “Quantitative Analysis of Spastic Hypertonia” by the Istituto Superiore della Sanitá during 1998–1999. He was the Clinical Scientific Leader of the INAIL project “International clinical survey over functional electrical stimulation.” He was the Scientific Project Leader of the Clinical Neurophysiology Unit of the project “Tecniche robotizzate per la valutazione ed il trattamento riabilitativo delle disabilitá motorie dell'arto superiore,” 2001-175, funded by the Italian Ministry of Health. He is currently a Neurologist and the Head of the Clinical Neurophysiology Unit, ”Salvatore Maugeri” Foundation, IRCCS, Rehabilitation Institute, Veruno, Italy. He has been published in the clinical and electrophysiological field of neuromuscular diseases and on the topic of stroke patients rehabilitation. His current research interests are in evaluation and treatment of upper limb disorders like spasticity and paresis. Dr. Pisano is a Member of the Italian Neurological Society and the Italian Clinical Neurophysiology Society. Giuseppe Minuco received the Dr. Eng. degree in mechanical engineering from the Politecnico Milano, Milan, Italy, in 1972, and a postgraduate degree in biomedical engineering from the Faculty of Medicine, Bologna, Italy, in 1975. He is currently Head of the Bioengineering Department, “Salvatore Maugeri” Foundation, IRCCS, Pavia, Italy. He is Chair of the Technical Scientific Committee of “CBIM” (Medical Informatics and Bioengineering Consortium) Pavia, Italy. He is Member of the Editorial Board of The Monaldi Archives for Chest Disease and of Giornale Italiano di Medicina del Lavoro ed Ergonomia. Has taught several courses in healthcare management. His main interests are in the fields of rehabilitation engineering, clinical engineering, medical informatics, and telemedicine. Paolo Dario received the Dr. Eng. degree in mechanical engineering from the University of Pisa, Pisa, Italy, in 1977. He is currently a Professor of Biomedical Robotics at the Scuola Superiore Sant'Anna, Pisa, Italy. He also teaches courses at the School of Engineering of the University of Pisa, and at the Campus Biomedico University, Rome, Italy. He has been a Visiting Professor at Brown University, Providence, RI, at the Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland, and at Waseda University, Tokyo, Japan. He was the founder of the Advanced Robotics Technologies and Systems (ARTS) Laboratory and is currently the co-cordinator of the Center for Research in Microengineering (CRIM) Laboratory of the Scuola Superiore Sant'Anna, where he supervises a team of about 70 researchers and Ph.D. students. He is also the Director of the Polo Sant'Anna Valdera and a Vice-Director of the Scuola Superiore Sant'Anna. His main research interests are in the fields of medical robotics, mechatronics, and micro/nanoengineering, and specifically in sensors and actuators for the above applications. He is the coordinator of many national and European projects, the editor of two books on the subject of robotics, and the author of more than 200 scientific papers (75 in ISI journals). He is Editor-in-Chief, Associate Editor, and Member of the Editorial Board of many international journals. Prof. Dario served as President of the IEEE Robotics and Automation Society during 2002–2003, and he is currently Co-Chair of the Technical Committees on Bio-robotics and of Robo-ethics of the same society. He is a Fellow of the European Society on Medical and Biological Engineering, and a recipient of many honors and awards, such as the Joseph Engelberger Award. He is also a Member of the Board of the International Foundation of Robotics Research (IFRR).     

实时多媒体流控中的预测最优均匀控制器设计

网络传输的抖动影响了VOD的播放质量,采用反馈控制机制进行实时多媒体流量控制是一种有效解决方法,但因实时多媒体流控模型及性能要求的特殊性,仅采用传统的反馈控制技术难以消除这一缺点.针对此问题,建立了实时多媒体反馈控制框架下的性能指标评价体系,设计了预测最优均匀控制算法.仿真实验表明,该算法有效地克服了网络传输抖动带来的不利影响,提高了VOD的播放质量.     

基于神经网络的实时专家控制系统及其PTA工业应用

以精对苯二甲酸结晶过程为研究对象。提出一种基于神经网络模型的实时专家控制系统．该方法利用神经网络建模技术获取对象的机理知识,通过对影响模型特性的多个变量进行分析,自动得到常规专家控制系统难于获取的定性、定量知识,并按分级递阶的启发式搜索机制,实现了对工业过程对象的实时控制．实际应用表明：该方法不但克服了以往专家系统知识获取的瓶颈,而且有效实现了人机对话的功能,便于现场操作和更改专家知识库,为化工过程的多变量控制提供了新的思路．     

A feedback scheduler for real-time controller tasks

The problem studied in this paper is how to distribute computing resources over a set of real-time control loops in order to optimize the total control performance. Two subproblems are investigated: how the control performance depends on the sampling interval, and how a recursive resource allocation optimization routine can be designed. Linear quadratic cost functions are used as performance indicators. Expressions for calculating their dependence on the sampling interval are given. An optimization routine, called a feedback scheduler, that uses these expressions is designed.     

Sensory interactive robot trajectory control using a real-time world model

A major consideration in the design of sensory interactive trajectory generation software for a Flight Telerobotic Servicer (FTS) is the availability and maintenance of a current model of the manipulator's world. The NASA/NBS Standard Reference Model for Telerobot Control System Architecture (NASREM), which has been adopted by NASA for control of the FTS, provides a logical computing architecture for telerobotics. It defines a hierarchical control system in which complex tasks are decomposed into progressively simpler subtasks, or objectives. It contains a hierarchy of world modeling modules which maintain the system's internal model of the manipulator and its world by continuously updating the model based upon sensory data. Each world modeling module contains support processes or functions which simultaneously and asynchronously support sensory processing and task decomposition. This paper discusses the role of world modeling in support of trajectory generation and execution. For sensory interactive robot motion control, the world modeling modules must operate rapidly so that the model of the world remains in registration with the real world.This paper discusses the world modeling modules of a hierarchical control system which facilitate sensory interactive trajectories by decoupling and supporting the sensory and manipulator planning processes. We define the types of information which should be included in the interfaces to the modules, as well as the modules' structure and function. Finally, we discuss the real-time implementation and experimental results of a particular sensory interactive algorithm performed in our laboratory.     

A neuro-fuzzy approach to real-time trajectory generation for robotic rehabilitation

This paper proposes a method for the design of a real-time neuro-fuzzy trajectory generator for the robotic rehabilitation of patients with upper limb dysfunction due to neurological diseases. The primary objective of the methodology is to assist therapists by allowing them to delegate repetitive therapy tasks to a mechatronic system. The trajectory generator is packaged as a platform-independent solution to facilitate the rehabilitation of patients using multiple manipulator configurations. The system utilizes a fuzzy-logic schema to introduce compliance into the human–robot interaction, and to allow the emulation of a wide variety of therapy techniques. This approach also allows for the fine-tuning of patient specific behaviour using linguistic variables. The rule base for the system is trained using a fuzzy clustering algorithm and applied to the experimental data gathered during traditional therapy sessions. The compliance rule base is combined with a hybrid neuro-fuzzy compensator to automatically tune the dynamics of the robot–patient interaction. Preliminary results indicate that the approach can accurately reproduce a prescribed patient/therapist interaction, validating the proposed approach.     

基于观测器的卷绕物收卷张力控制系统的研究

本文以一类卷绕系统的收卷过程为研究对象,建立了其动态数学模型,提出了一种基于张力观测器的新型控制方案。笔者根据辊的动态转矩平衡方程式,利用系统原有的电机控制和速度检测信号,将观测的张力值作为反馈,构成张力闲环,从而实现无传感器反馈控制。最后,对这种方案进行了仿真。结果表明,本文提出的方案完全可以达到常规规方案的动态性能,具有较高的稳态精度。这充分说明了该算法是可行的。     

基于SoPC的实时说话人识别控制器

运用软硬件协同设计,在DE2-70开发板上实现了一个基于SoPC的实时说话人识别控制器,控制器有很好的实时性和良好的识别性能。控制器的语音特征参数采用线性预测倒谱系数(LPCC),匹配算法采用动态时间规整算法(DTW)。     

Global Control of Robotic Highway Safety Markers: A Real-time Solution

This paper presents the design and implementation of a real-time solution for the global control of robotic highway safety markers. Problems addressed in the system are: (1) poor scalability and predictability as the number of markers increases, (2) jerky movement of markers, and (3) misidentification of safety markers caused by objects in the environment.An extensive analysis of the system and two solutions are offered: a basic solution and an enhanced solution. They are built respectively upon two task models: the periodic task model and the variable rate execution (VRE) task model. The former is characterized by four static parameters: phase, period, worst case execution time and relative deadline. The latter has similar parameters, but the parameter values are allowed to change at arbitrary times.The use of real-time tasks and scheduling techniques solve the first two problems. The third problem is solved using a refined Hough transform algorithm and a horizon scanning window. The approach decreases the time complexity of traditional implementations of the Hough transform with only slightly increased storage requirements.Supported, in part, by grants from the National Science Foundation (CCR-0208619 and CNS-0409382) and the National Academy of Sciences Transportation Research Board-NCHRP IDEA Program (Project #90).Jiazheng Shi received the B.E. and M.E. degrees in electrical engineering from Beijing University of Posts and Telecommunications in 1997 and 2000, respectively. In 2000, he worked with the Global Software Group, Motorola Inc. Currently, he is a Ph.D. candidate in the Computer Science and Engineering Department at the University of Nebraska–Lincoln. His research interests are automated human face recognition, image processing, computer vision, approximate theory, and linear system optimization.Steve Goddard is a J.D. Edwards Associate Professor in the Department of Computer Science & Engineering at the University of Nebraska–Lincoln. He received the B.A. degree in computer science and mathematics from the University of Minnesota (1985). He received the M.S. and Ph.D. degrees in computer science from the University of North Carolina at Chapel Hill (1995, 1998).His research interests are embedded, real-time and distributed systems with emphases in high assurance systems engineering and real-time, rate-based scheduling theory.Anagh Lal received a B.S. degree in Computer Science from the University of Mumbai (Bombay), Mumbai, in 2001. He is currently a graduate research assistant at the University of Nebraska–Lincoln working on a M.S. in Computer Science, and a member of the ConSystLab. His research interests lie in Databases, Constraint Processing and Real Time Systems. Anagh will be graduating soon and is looking for positions at research institutions.Jason Dumpert received a B.S. degree in electrical engineering from the University of Nebraska–Lincoln in 2001. He received a M.S. degree in electrical engineering from the University of Nebraska-Lincoln in 2004. He is currently a graduate research assistant at the University of Nebraska-Lincoln working on a Ph.D. in biomedical engineering. His research interests include mobile robotics and surgical robotics.Shane M. Farritor is an Associate Professor in the University of Nebraska–Lincolns Department of Mechanical Engineering. His research interests include space robotics, surgical robotics, biomedical sensors, and robotics for highway safety. He holds courtesy appointments in both the Department of Surgery and the Department of Orthopaedic Surgery at the University of Nebraska Medical Center, Omaha. He serves of both the AIAA Space Robotics and Automation technical committee and ASME Dynamic Systems and Control Robotics Panel. He received M.S. and Ph.D. degrees from M.I.T.     

驾驶员在环的SUV防侧翻控制器实时仿真设计

运用驾驶员在回路实时仿真系统设计SUV汽车防侧翻差动制动控制器并验证其有效性和可靠性。根据驾驶员的逻辑判断,得到理想的汽车行驶状态,当汽车行驶偏离理想值时,用控制系统来纠正SUV的横摆力矩。仿真实验在加拿大安省理工大学的汽车模拟器上进行,通过Fishhook和双移线工况对设计的控制器性能进行研究分析,对比控制前后对汽车侧向稳定性能的改善效果。仿真结果表明,所设计的控制器能有效提高汽车侧向稳定性和可操纵性。     

Windows平台下的实时仿真计算机系统PCRTSim

普通微型计算机由于各种相互兼容的标准硬件及丰富的应用软件支持而获得了广泛的应用,但它们之上往往都是运行多任务、多用户的Windows操作系统,一般不能满足半实物仿真的实时性要求。详细介绍了一个Windows平台下的实时仿真计算机系统PCRTSim,重点研究了PCRTSim下的实时时钟获取问题、帧时间不稳定问题,提出了保证实时仿真帧时间的具体思路,并通过一个简单例子探讨了PCRTSim的具体应用。     

Evolutionary learning of a fuzzy controller for wall-following behavior in mobile robotics

The design of fuzzy controllers for the implementation of behaviors in mobile robotics is a complex and highly time-consuming task. The use of machine learning techniques such as evolutionary algorithms or artificial neural networks for the learning of these controllers allows to automate the design process. In this paper, the automated design of a fuzzy controller using genetic algorithms for the implementation of the wall-following behavior in a mobile robot is described. The algorithm is based on the iterative rule learning approach, and is characterized by three main points. First, learning has no restrictions neither in the number of membership functions, nor in their values. In the second place, the training set is composed of a set of examples uniformly distributed along the universe of discourse of the variables. This warrantees that the quality of the learned behavior does not depend on the environment, and also that the robot will be capable to face different situations. Finally, the trade off between the number of rules and the quality/accuracy of the controller can be adjusted selecting the value of a parameter. Once the knowledge base has been learned, a process for its reduction and tuning is applied, increasing the cooperation between rules and reducing its number.     

卷绕张力控制系统的建模及张力观测器的设计

在物料传送系统中,如何对物料张力和线速度进行独立的控制,一直是关注的焦点问题;以典型的卷绕张力系统为研究对象,建立了其动态数学模型;详细地分析了基于传感器张力反馈的常规控制方案,并在此基础上提出了一种基于张力观测器的新型控制方案;它根据辊的动态转矩平衡方程式,利用系统原有的电机控制和速度检测信号,将观测的张力值作为反馈,构成张力闭环,从而实现无传感器反馈控制;最后,对两种方案进行了仿真比较,结果表明,提出的方案完全可以达到常规方案的动态性能,而且具有更高的稳态精度,这充分说明了该算法是可行的.     

Force Control of Robotic Manipulators Using a Fuzzy Predictive Approach

This paper proposes a force control strategy for robotic manipulators considering a non-rigid environment described by a nonlinear model. This approach uses a fuzzy predictive algorithm to generate, in an optimal way, the reference or virtual position to the classical impedance controller in order to apply a desired force profile on the environment. The main advantage of this control strategy is the possibility of including a nonlinear model of the environment in the controller design in a straightforward way, improving the global force control performance, especially in non-rigid environments. Moreover, in order to reduce the oscillations on the optimized reference position a fuzzy scaling machine is included on the force control strategy. The performance of the force control scheme is illustrated for a two degree-of-freedom PUMA 560 robot, which end-effector is forced to move along a flat surface located on the vertical plane. The simulation results obtained with the fuzzy control scheme reveal significant improvement in the force tracking performance, when compared to the impedance control with force tracking in non-rigid environments.     

实时控制系统中数据的实时分片存储

为了在不影响实时控制系统响应时间的前提下实时地保存数据,提出了一种基于分片的数据实时存储方式.通过在实时控制系统中添加存储节点,在实时控制的过程中,实时节点将数据按时间分片,传给存储节点,存储节点采用分片存储的方式保存到存储系统中.这种方式只需要占用实时控制节点很少的控制周期时间,结合新增的存储节点完成对实时数据的存储,能在控制过程中实时读取分析数据.该方式应用于东方超环(EAST)等离子体控制系统上,能够较好的实现对长脉冲放电和未来的稳态放电实验数据进行实时的存储和读取分析,也能为其他实时控制系统的数据的实时存储提供借鉴.     

GA-pattern matching-based manipulator control system for real-time visual servoing

_—In robotic applications, tasks of picking and placing are the most fundamental ones. Also, for a robot manipulator, the recognition of its working environment is one of the most important issues to do intelligent tasks, since this aptitude enables it to work in a variable environment. This paper presents a new control strategy for robot manipulators, which utilizes visual information to direct the manipulator in its working space, to pick up an object of known shape, but with arbitrary position and orientation. During the search for an object to be picked up, vision-based control by closed-loop feedback, referred to as visual servoing, is performed to obtain the motion control of the manipulator hand. The system employs a genetic algorithm (GA) and a pattern matching technique to explore the search space and exploit the best solutions by this search technique. The control strategy utilizes the found results of GA-pattern matching in every step of GA evolution to direct the manipulator towards the target object. We named this control strategy step-GA-evnlution. This control method can be applied for manipulator real-time visual servoing and solve its path planning problem in real-time, i.e. in order for the manipulator to adapt the execution of the task by visual information during the process execution. Simulations have been performed, using a two-link planar manipulator and three image models, in order to find which one is the best for real-time visual servoing and the results show the effectiveness of the control method.