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RETRACTED ARTICLE: Support vector regression methodology for prediction of input displacement of adaptive compliant robotic gripper

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Applied Intelligence 2014年第3期41卷 887-896页

作者： Dalibor Petković Shahaboddin Shamshirband Hadi Saboohi Tan Fong Ang Nor Badrul Anuar Nenad D. Pavlović Faculty of Mechanical Engineering Deparment for Mechatronics and Control University of Niš Niš Serbia Department of Computer Science Chalous Branch Islamic Azad University (IAU) Chalous Iran Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Department of Information System Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Computer Engineering Department Islamic Azad University of Karaj Karaj Iran

The prerequisite for new versatile grippers is the capability to locate and perceive protests in their surroundings. It is realized that automated controllers are profoundly nonlinear frameworks, and a faultless numerical model is hard to get, in this way making it troublesome to control utilizing tried and true procedure. Here, a design of an adaptive compliant gripper is presented. This design of the gripper has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize specific shapes of the grasping objects. Since the conventional control strategy is a very challenging task, soft computing based controllers are considered as potential candidates for such an application. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict optimal inputs displacement of the gripper according to experimental tests and shapes of grasping objects. Instead of minimizing the observed training error, SVR poly and SVR rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR approach compared to other soft computing methodology.

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Effective approaches to Adaptive Collaboration

Effective approaches to Adaptive Collaboration

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IEEE International Conference on Networking, Sensing and control

作者： Yin Sheng Haibin Zhu Xianzhong Zhou Luming Feng Department of Control and System Engineering Nanjing University Jiangsu China Department of Computer Science and Mathematics Nipissing University North Bay Ontario Canada

Adaptive Collaboration (AC) is essential for group performance optimization in collaborative systems. This paper begins by introducing AC within the context of solving a real world problem. Next, AC problems are formalized based on the Environment-Class, Agent, Role, Group, and Object (E-CARGO) model. Three algorithms are then proposed for solving AC problems. These algorithms are based on three different scenarios: the current group state, the group state after a definite period of time and the group state all over the collaboration, respectively. Experiments are developed to analyze the performance of each proposed algorithm. Results indicate that the proposed algorithms perform better than static collaboration.

关键词： Collaboration

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Low-cost remote laboratories for renewable energy in distance education

Low-cost remote laboratories for renewable energy in distanc...

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International Conference on Remote engineering and Virtual Instrumentation (REV)

作者： Llanos Tobarra Salvador Ros Roberto Hernández Rafael Pastor Antonio Robles-Gómez Agustín C. Cammero Manuel Castro Control and Communication System Department Spanish University for Distance Education Madrid Spain Control and Communication System Department UNED - Spanish University for Distance Education Madrid Spain Electrical and Computer Engineering Department Spanish University for Distance Education Madrid Spain

Remote laboratories are nowadays essential in distance learning, as our case is, since students are not able to use face-to-face traditional laboratories. These remote laboratories can be employed by teacher within virtual classrooms, so that students can carry out their on-line experiments from anywhere and at anytime. The main drawback of these kinds of laboratories is their cost; this is more noticeable in the field of renewable energy. For this reason, this work proposes the use of low-cost remote laboratories, aimed at the study of solar and wind renewable energy. The described remote laboratory is based on using the popular robotic kit, named Lego Mindstorms NXT v2.0. robotic kit, which allows teachers to have flexibility when designing the laboratory and adapt it to the educational necessities of a course. The programming of these laboratories has been performed by using RESTful web services with Lab VIEW, a novel approach that enables users the creation of multiplatform laboratories.

关键词： Barium Hafnium Conferences Instruments DH-HEMTs

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On overcoming limitations of a class of linear systems with first-order reset elements

On overcoming limitations of a class of linear systems with ...

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World Congress on Intelligent control and Automation (WCICA)

作者： Guanglei Zhao Jingcheng Wang Kang Li Department of Automation Key Laboratory of System Control and Information Processing China Electrical Engineering and Computer Science Queens University Belfast UK

This paper considers using reset control to improve transient performance and overcome some fundamental limitations of linear systems. First, an auxiliary system is presented, then, based on which, a new reset control model is proposed, such that the non-overshoot performance specification can be met for any minimum phase relative degree one plants, the results imply some limitations of linear systems are overcome and clearly illustrate the advantages of reset control. A numerical example is given to show the effectiveness.

关键词： Closed loop systems Stability analysis Gold Linear systems Steady-state Educational institutions

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RETRACTED ARTICLE: Soft computing methodologies for estimation of bridge girder forces with perforations under tsunami wave loading

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Bulletin of Earthquake engineering 2014年第3期13卷 935-952页

作者： Akib, Shatirah Rahman, Sadia Shamshirband, Shahaboddin Petković, Dalibor Department of Civil Engineering University of Malaya Kuala Lumpur Malaysia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Department of Computer Science Chalous Branch Islamic Azad University (IAU) Chalous Iran Department for Mechatronics and Control Faculty of Mechanical Engineering University of Niš Nis Serbia

Tsunamis pose a great threat to coastal infrastructures. Bridges without adequate provisions for earthquake and tsunami loading generally are vulnerable when a tsunami occurs. During the last two disastrous tsunami events (i.e., the tsunami in the Indian Ocean and the tsunami that struck Japan), many bridges were damaged by the waves created by the tsunamis. In this paper, in order to address this crucial problem, we used soft computing techniques to design and develop a process that simulates the effects of perforations in the girders of bridges on reducing the forces applied on the bridge when a tsunami occurs. Soft computing methods have very good learning and prediction capabilities, which make it an effective tool for dealing with the uncertainties encountered when waves are generated by a tsunami. Laboratory experiments were conducted to acquire a better understanding of the effects of the factors involved and to check the data required for the soft computing methods. In order to predict the effects of perforations in the girder of a bridge on force reduction, novel intelligent soft computing schemes, support vector regression (SVR), and adaptive neuro-fuzzy inference system (ANFIS) were investigated. In this study, the polynomial, linear, and radial basis function were used as the kernel function of the SVR to estimate the effects of perforations in a girder of a bridge. The performances of the proposed estimators were confirmed by simulation results. The SVR results were compared with the ANFIS results, and we observed that an improvement in predictive accuracy and the ability to generalize were achieved by the ANFIS approach.

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A New Class of Learning Automata for Selecting an Optimal Subset

A New Class of Learning Automata for Selecting an Optimal Su...

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IEEE International Conference on systems, Man, and Cybernetics

作者： JunQi Zhang ZeZhou Li Qi Kang MengChu Zhou Key Laboratory of Embedded System and Service Computing Ministry of Education Department of Computer Science and Technology Tongji University Department of Control Science and Engineering Tongji University Department of Electrical and Computer Engineering New Jersy Institute of Technology

ISBN: (纸本)9781479938414

Interacting with a random environment, Learning Automata (LAs) are automata that, generally, have the task of learning the optimal action based on responses from the environment. Distinct from the traditional goal of Learning Automata to select only the optimal action out of a set of actions, this paper considers a multiple-action selection problem and proposes a novel class of Learning Automata for selecting an optimal subset of actions. Their objective is to identify the optimal subset: the top k out of r actions. Based on conventional continuous pursuit and discretized pursuit learning schemes, this paper introduces four pursuit learning schemes for selecting the optimal subset, called continuous equal pursuit, discretized equal pursuit, continuous unequal pursuit and discretized unequal pursuit learning schemes, respectively. In conjunction with a reward-inaction learning paradigm, the above four schemes lead to four versions of pursuit Learning Automata for selecting the optimal subset. The simulation results present a quantitative comparison between them.

关键词： Learning Automata Optimal subset Pursuit algorithm

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Implementation and test of human-operated and human-like adaptive impedance controls on Baxter robot

Implementation and test of human-operated and human-like ada...

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15th Annual Conference on Advances in Autonomous Robotics systems, TAROS 2014

作者： Liang, Peidong Yang, Chenguang Wang, Ning Li, Zhijun Li, Ruifeng Burdet, Etienne Centre for Robotics and Neural Systems School of Computing and Mathematics Plymouth University United Kingdom MOE Key Lab. of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology China State Key Laboratory of Robotics and System Harbin Institute of Technology China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Department of Bioengineering Imperial College of Science Technology and Medicine London United Kingdom

ISBN: (纸本)9783319104003

This paper presents an improved method to teleoperate impedance of a robot based on surface electromyography (EMG) and test it experimentally. Based on a linear mapping between EMG amplitude and stiffness, an incremental stiffness extraction method is developed, which uses instantaneous amplitude identified from EMG in a high frequency band, compensating for non-linear residual error in the linear mapping and preventing muscle fatigue from affecting the control. Experiments on one joint of the Baxter robot are carried out to test the approach in a disturbance attenuation task, and to compare it with automatic human-like impedance adaptation. The experimental results demonstrate that the new human operated impedance method is successful at attenuating disturbance, and results similarly to as automatic disturbance attenuation, thus demonstrating its efficiency. © 2014 Springer International Publishing.

关键词： Stiffness

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On infinite time performance of nonlinear model predictive controllers 19

On infinite time performance of nonlinear model predictive c...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Cai, Xin Li, Shaoyuan Li, Ning Li, Kang Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China School of Electronics Electrical Engineering and Computer Science Queen's University Belfast BelfastBT7 1NN United Kingdom

ISBN: (纸本)9783902823625

This paper addresses the problem of infinite time performance of model predictive controllers applied to constrained nonlinear systems. The total performance is compared with a finite horizon optimal cost to reveal performance limits of closed-loop model predictive control systems. Based on the Principle of Optimality, an upper and a lower bound of the ratio between the total performance and the finite horizon optimal cost are obtained explicitly expressed by the optimization horizon. The results also illustrate, from viewpoint of performance, how model predictive controllers approaches to infinite optimal controllers as the optimization horizon increases. © IFAC.

关键词： controllers

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Statistical Validation of Automatic Methods for Hippocampus Segmentation in MR Images of Epileptic Patients

Statistical Validation of Automatic Methods for Hippocampus ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Mohammad-Parsa Hosseini Mohammad R. Nazem-Zadeh Dario Pompili Hamid Soltanian-Zadeh Department of Electrical and Computer Engineering Rutgers University Medical Image Analysis Lab Radiology Department Henry Ford Health System Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran

ISBN: (纸本)9781424479276

Hippocampus segmentation is a key step in the evaluation of mesial Temporal Lobe Epilepsy (mTLE) by MR images. Several automated segmentation methods have been introduced for medical image segmentation. Because of multiple edges, missing boundaries, and shape changing along its longitudinal axis, manual outlining still remains the bench-mark for hippocampus segmentation, which however, is impractical for large datasets due to time constraints. In this study, four automatic methods, namely FreeSurfer, Hammer, Automatic Brain Structure Segmentation (ABSS), and LocalInfo segmentation, are evaluated to find the most accurate and applicable method that resembles the bench-mark of hippocampus. Results from these four methods are compared against those obtained using manual segmentation for T1-weighted images of 157 symptomatic mTLE patients. For performance evaluation of automatic segmentation, Dice coefficient, Hausdorff distance, Precision, and Root Mean Square (RMS) distance are extracted and compared. Among these four automated methods, ABSS generates the most accurate results and the reproducibility is more similar to expert manual outlining by statistical validation. By considering p-value<0.05, the results of performance measurement for ABSS reveal that, Dice is 4%, 13%, and 17% higher, Hausdorff is 23%, 87%, and 70% lower, precision is 5%, -5%, and 12% higher, and RMS is 19%, 62%, and 65% lower compared to LocalInfo, FreeSurfer, and Hammer, respectively.

关键词： Segmentation Hippocampus Magnetic Resonance Imaging (MRI) Comparison Epilepsy

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Managed N-gram language model based on Hadoop framework and a Hbase tables

Managed N-gram language model based on Hadoop framework and ...

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The International Conference on Informatics and systems (INFOS)

作者： Tahani Mahmoud Allam Alsayed Abdelhameed Sallam Hatem M. Abdullkader Computer and Automatic Control Department Faculty of Engineering Tanta University Tanta Egypt Information System Department Faculty of Computers and Information Menofia University Menofia Egypt

N-grams are a building block in natural language processing and information retrieval. It is a sequence of a string data like contiguous words or other tokens in text documents. In this work, we study how N-gram can be computed efficiently using a MapReduce for distributed data processing and a distributed database named Hbase This technique is applied to construct the training and testing processes using Hadoop MapReduce framework and Hbase. We proposed to focus on the time cost and storage size of the model and exploring different structures of Hbase table. By constructing and comparing a different table structures on training 100 million words for unigram, bigram and trigram models we suggest a table based on half ngram structure is a more suitable choice for distributed language model. The results of this work can be applied in the cloud computing and other large scale distributed language processing areas.

关键词： Computational modeling Training Smoothing methods Context Testing Informatics Distributed computing

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