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Proceedings of the IEEE Internatinal Symposium on Intelligent Control最新文献

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An optimal design of PD-type iterative learning control with monotonic convergence 具有单调收敛的pd型迭代学习控制的优化设计
Proceedings of the IEEE Internatinal Symposium on Intelligent Control Pub Date : 2002-10-27 DOI: 10.1109/ISIC.2002.1157738
Y. Chen, K. Moore
{"title":"An optimal design of PD-type iterative learning control with monotonic convergence","authors":"Y. Chen, K. Moore","doi":"10.1109/ISIC.2002.1157738","DOIUrl":"https://doi.org/10.1109/ISIC.2002.1157738","url":null,"abstract":"Iterative learning control (ILC) is a technique to make use of the repetitiveness of the tasks a system is commanded to execute in a fixed finite time interval. In this paper, we assume that a measured finite impulse response series of the plant to be controlled is available. We present an optimal design procedure for the commonly used PD-type ILC updating law. The monotonic convergence in a suitable norm topology other than the exponentially weighted sup-norm is emphasized. For practical reasons, an averaged difference formula for a numerical derivative estimate is preferred over the conventional one step backward difference method for smoothing out the high frequency noise. From the analysis, we show a trade-off between noise suppression and the rate of monotonic convergence of the ILC process.","PeriodicalId":228502,"journal":{"name":"Proceedings of the IEEE Internatinal Symposium on Intelligent Control","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124794637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 71
Real-time fuzzy PI + PD control for an underactuated robot 欠驱动机器人的实时模糊PI + PD控制
Proceedings of the IEEE Internatinal Symposium on Intelligent Control Pub Date : 2002-10-27 DOI: 10.1109/ISIC.2002.1157752
E. Sánchez, Victor Flores
{"title":"Real-time fuzzy PI + PD control for an underactuated robot","authors":"E. Sánchez, Victor Flores","doi":"10.1109/ISIC.2002.1157752","DOIUrl":"https://doi.org/10.1109/ISIC.2002.1157752","url":null,"abstract":"In this paper a new PI + PD fuzzy controller, which includes a dynamic switching fuzzy system (DFSFS), is applied to swing-up an underactuated mechanism: the pendubot. This mechanism consists of a double pendulum actuated only at the first joint. This new controller and its real-time application to the pendubot constitute our original contributions.","PeriodicalId":228502,"journal":{"name":"Proceedings of the IEEE Internatinal Symposium on Intelligent Control","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126142080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
On the intelligent control of a rotary crane, neural network and fuzzy logic approaches 基于神经网络和模糊逻辑的旋转起重机智能控制研究
Proceedings of the IEEE Internatinal Symposium on Intelligent Control Pub Date : 2002-10-27 DOI: 10.1109/ISIC.2002.1157828
Amel Ouezri, N. Derbel
{"title":"On the intelligent control of a rotary crane, neural network and fuzzy logic approaches","authors":"Amel Ouezri, N. Derbel","doi":"10.1109/ISIC.2002.1157828","DOIUrl":"https://doi.org/10.1109/ISIC.2002.1157828","url":null,"abstract":"This paper deals with the determination of the optimal control strategies of a rotary crane. Such system is represented by a sixth order nonlinear mathematical model. The proposed idea is based on the decomposition of the system into two interconnected subsystems which are linear with respect to their state and control vectors. The nonlinearities are located in the interconnexion terms. In this context, local feedback gains can be computed by solving a nonlinear Riccati equation, whereas, the local gains depend on the state vector of the other subsystem. Within this approach, a fuzzy logic system and a neural network have been constructed in order to identify these gains. Simulation results show the high performances of the proposals.","PeriodicalId":228502,"journal":{"name":"Proceedings of the IEEE Internatinal Symposium on Intelligent Control","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128016414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Fourier series learning of biped walking motion 双足行走运动的傅立叶级数学习
Proceedings of the IEEE Internatinal Symposium on Intelligent Control Pub Date : 2002-10-27 DOI: 10.1109/ISIC.2002.1157737
T. Kuc, Seungmin Baek, H. Lee, J. O. Kim
{"title":"Fourier series learning of biped walking motion","authors":"T. Kuc, Seungmin Baek, H. Lee, J. O. Kim","doi":"10.1109/ISIC.2002.1157737","DOIUrl":"https://doi.org/10.1109/ISIC.2002.1157737","url":null,"abstract":"A learning controller is presented for repetitive walking motion of biped robot. The learning control scheme learns the approximate inverse dynamics input of biped walking robot and uses the learned input pattern to generate an input profile of different walking motion. In the learning controller, the PID feedback controller takes part in stabilizing the transient response of robot dynamics while the feedforward learning controller plays a role in computing the desired actuator torques for feedforward nonlinear dynamics compensation in steady state. It is shown that all the error signals in the learning control system are bounded and the robot motion trajectory converges to the desired one asymptotically. The proposed learning control scheme is shown to be effective through a computer simulation with a 12-DOF biped robot.","PeriodicalId":228502,"journal":{"name":"Proceedings of the IEEE Internatinal Symposium on Intelligent Control","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122974905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Discrepancy as a quality measure for avoiding classification bias 差异作为避免分类偏差的质量度量
Proceedings of the IEEE Internatinal Symposium on Intelligent Control Pub Date : 2002-10-27 DOI: 10.1109/ISIC.2002.1157819
K. Iwata, Naohiro Ishii
{"title":"Discrepancy as a quality measure for avoiding classification bias","authors":"K. Iwata, Naohiro Ishii","doi":"10.1109/ISIC.2002.1157819","DOIUrl":"https://doi.org/10.1109/ISIC.2002.1157819","url":null,"abstract":"This paper discusses how to create initial data to achieve a good performance on active learning of multilayer perceptrons. The initial training data plays an important role for active learning performance, because any active learning algorithm generates additional training data based on existing data. In this paper on active learning of a multi-layer perceptron in the case of little initial data, we verify an effect of the bias of the initial data using discrepancy. Discrepancy is a measure of the uniformity of data distribution. We then discuss a method for generation of initial data using a low-discrepancy sequence. In our experimental results of the classification problem, we found that initial data with a low discrepancy avoids classification bias. Hence, discrepancy as a measure is a quality guide to avoid classification bias, and low-discrepancy sequences provide a good strategy to generate initial data on active learning of multi-layer perceptrons.","PeriodicalId":228502,"journal":{"name":"Proceedings of the IEEE Internatinal Symposium on Intelligent Control","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124053754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Philips CFT RoboCup platform selection 飞利浦CFT机器人世界杯平台选择
Proceedings of the IEEE Internatinal Symposium on Intelligent Control Pub Date : 2002-10-27 DOI: 10.1109/ISIC.2002.1157866
A. Peijnenburg, G. P. Veldhuis, T.P.H. Warmerdam
{"title":"Philips CFT RoboCup platform selection","authors":"A. Peijnenburg, G. P. Veldhuis, T.P.H. Warmerdam","doi":"10.1109/ISIC.2002.1157866","DOIUrl":"https://doi.org/10.1109/ISIC.2002.1157866","url":null,"abstract":"An enthusiastic team from Philips Center for Industrial Technology (CFT) has decided to participate In the RoboCup competition. In a hobby project, a team of autonomous soccer playing robots has been designed and built. This paper describes the main design choices behind the kinematic configuration and some of Its consequences for motion control.","PeriodicalId":228502,"journal":{"name":"Proceedings of the IEEE Internatinal Symposium on Intelligent Control","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120893339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Residual-gradient-based neural reinforcement learning for the optimal control of an acrobot 基于残差梯度的神经强化学习在机器人最优控制中的应用
Proceedings of the IEEE Internatinal Symposium on Intelligent Control Pub Date : 2002-10-27 DOI: 10.1109/ISIC.2002.1157857
Xin Xu, Han-gen He
{"title":"Residual-gradient-based neural reinforcement learning for the optimal control of an acrobot","authors":"Xin Xu, Han-gen He","doi":"10.1109/ISIC.2002.1157857","DOIUrl":"https://doi.org/10.1109/ISIC.2002.1157857","url":null,"abstract":"Based on the idea of dynamic programming, reinforcement learning (RL) has become an important model-free method to solve difficult optimal control problems. In this paper, a novel neural RL method is proposed to solve the time-optimal control problem of a class of under-actuated robots, which is called the acrobot. The RL method uses a modified residual gradient reinforcement learning algorithm called RGNP (residual gradient with nonstationary policy). The RGNP algorithm not only has guaranteed convergence under certain conditions but also can ensure the performance of the approximated optimal policy, which is superior to the previous residual gradient algorithms. Simulation results of the learning control of the acrobot illustrate the effectiveness of the proposed method.","PeriodicalId":228502,"journal":{"name":"Proceedings of the IEEE Internatinal Symposium on Intelligent Control","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131213654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 17
4D/RCS sensory processing and world modeling on the Demo III experimental unmanned ground vehicles Demo III实验无人地面车辆的4D/RCS感官处理和世界建模
Proceedings of the IEEE Internatinal Symposium on Intelligent Control Pub Date : 2002-10-27 DOI: 10.1109/ISIC.2002.1157879
J. Albus, K. Murphy, A. Lacaze, S. Legowik, S. Balakirsky, T. Hong, M. Shneier, E. Messina
{"title":"4D/RCS sensory processing and world modeling on the Demo III experimental unmanned ground vehicles","authors":"J. Albus, K. Murphy, A. Lacaze, S. Legowik, S. Balakirsky, T. Hong, M. Shneier, E. Messina","doi":"10.1109/ISIC.2002.1157879","DOIUrl":"https://doi.org/10.1109/ISIC.2002.1157879","url":null,"abstract":"The success of the Army Research Lab Demo III project at Ft. Indiantown Gap in November, 2001 suggests that autonomous driving by unmanned ground vehicles under tactical conditions is achievable within this decade. Laser range imaging sensors have been developed to provide dense range images that enable autonomous vehicles to build an internal geometric model of the terrain and objects within the environment. Real-time value-based planning algorithms have been developed that enable the autonomous vehicle to replan its intended path through the environment many times per second. The 4D/RCS system architecture has been validated as an open, modular, hierarchical, multi-resolutional integration architecture and design methodology for unmanned ground vehicles.","PeriodicalId":228502,"journal":{"name":"Proceedings of the IEEE Internatinal Symposium on Intelligent Control","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131214446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Application of a model-based fault detection and diagnosis using parameter estimation and fuzzy inference to a DC-servomotor 基于参数估计和模糊推理的模型故障检测与诊断在直流伺服电机中的应用
Proceedings of the IEEE Internatinal Symposium on Intelligent Control Pub Date : 2002-10-27 DOI: 10.1109/ISIC.2002.1157861
M. Abidin, R. Yusof, Marzuki Kahlid, S. Amin
{"title":"Application of a model-based fault detection and diagnosis using parameter estimation and fuzzy inference to a DC-servomotor","authors":"M. Abidin, R. Yusof, Marzuki Kahlid, S. Amin","doi":"10.1109/ISIC.2002.1157861","DOIUrl":"https://doi.org/10.1109/ISIC.2002.1157861","url":null,"abstract":"Fault detection and diagnosis are very much needed in many industrial applications. One of the most popular scheme is the model-based fault diagnostic. Recently, artificial intelligence techniques have been found to be suitable for fault detection and diagnosis and a variety of techniques have been proposed in this area. However, only few applications and real time implementation of the schemes have been reported. In this paper, we use a fault detection and diagnostic scheme based on the model-based approach using parameter estimation and fuzzy inference and experimented it on a DC motor servo trainer. The model of the plant is obtained using the recursive least squares parameter estimation technique, and fuzzy inference is used for the interpretation of the fault. Several faults have been identified on the system. The faults are then simulated on the motor and experiments are carried out to diagnose the types of faults. Experiments show the effectiveness of the proposed technique for real time applications.","PeriodicalId":228502,"journal":{"name":"Proceedings of the IEEE Internatinal Symposium on Intelligent Control","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123831038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
On a definition of task oriented intelligent control 面向任务的智能控制的定义
Proceedings of the IEEE Internatinal Symposium on Intelligent Control Pub Date : 2002-10-27 DOI: 10.1109/ISIC.2002.1145668
M. Cotsaftis
{"title":"On a definition of task oriented intelligent control","authors":"M. Cotsaftis","doi":"10.1109/ISIC.2002.1145668","DOIUrl":"https://doi.org/10.1109/ISIC.2002.1145668","url":null,"abstract":"To delegate decisional power to a control system, it is shown that information flux is required in parallel to power flux. A natural setting is obtained by limiting the decision to task accomplishment and by extending system control so that both dynamical and decisional control levels can harmoniously communicate through a common element based on the system trajectory as a whole, and can be explicitly expressed in terms of system parameters.","PeriodicalId":228502,"journal":{"name":"Proceedings of the IEEE Internatinal Symposium on Intelligent Control","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122152977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
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