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International Conference on control, Instrumentation, and Automation

作者： Pouya Badri Elyar Zavary Mahdi Sojoodi Advanced Control Systems Laboratory School of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran

ISBN: (数字)9781728158150

ISBN: (纸本)9781728158167

In this paper, a fixed-order procedure is presented utilizing convex optimization and linear matrix inequalities (LMIs) to control a quarter car uncertain active suspension system. Our purpose is to design a low-order robust controller that keeps the desired design specifications besides the simplicity of the implementation. In our model, the system is influenced by the non-linear disturbance of the road surface, and the polytopic uncertainty model for state matrices of the system is utilized to cover the uncertainties of the model and the delay caused by the dynamic of the system. In this paper, a specific form of a positive definite matrix is used to overcome the complexity of rank minimization constraints. The proposed controller is considered with the most general state-space representation of linear systems which can be resulted by solving appropriate LMI constraints utilizing available efficient solving methods. Our proposed controller benefits from the dynamic property, independency of all individual states of the system, being of arbitrary order, and robustness against model uncertainty simultaneously. Eventually, a simulation example is presented to illustrate the correctness and effectiveness of the proposed method and obtained results for different orders that are compared with each other and also with that of a similar full-order method.

关键词： Suspensions Uncertainty Mathematical model Robustness Automobiles control systems Vehicle dynamics

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Optimal gait design for the lower extremity exoskeleton (Exoped)

Optimal gait design for the lower extremity exoskeleton (Exo...

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International Conference on control, Instrumentation, and Automation

作者： Jafar Kazemi Elyar Zavary Sadjaad Ozgoli Advanced Control Systems Laboratory School of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran

ISBN: (数字)9781728158150

ISBN: (纸本)9781728158167

Assistive robots have been grown in recent years and joints' moving pattern is one of the important issues in these robots. The predefined trajectory for the robot brings some stability difficulties for the users. This paper introduces a systematic way to produce an optimal gait for the controller of the lower extremity exoskeleton. This optimal gait producing strategy releases us from the exhausting procedure of walking pattern capture in different paces which requires various devices and motion analysis lab. A feedback-controlled system is defined which enables us to change walking parameters during steps with a smooth walking pattern which is of vital importance for the patients in these kinds of robots. This goal has been achieved by solving an optimal control problem, and the cost function of this optimization problem is obtained thorough walking limitations. Implementation on the Exoped robot verifies the performance of the proposed walking trajectory planning method in this paper.

关键词： Legged locomotion Trajectory Exoskeletons Boundary conditions Planning Cost function

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Variable Selection Method Based on Partial Mutual Information and Its Application to NOx Emission Prediction

Variable Selection Method Based on Partial Mutual Informatio...

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第三十九届中国控制会议

作者： QIN Tianmu ZHANG Jinzhe YOU Mo YANG Tingting North China Electric Power Research Institute Co. Ltd. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer EngineeringNorth China Electric Power University

Data-driven modeling methods are widely used in industrial processes as the foundation of control and *** selection of optimal variable set plays an important role in model *** order to enhance the model prediction accuracy,a partial mutual information(PMI) method was proposed to select the optimal variable *** were used to validate the effectiveness of PMI ***,PMI method was applied to select main influencing factors of NOx emission of coal-fired boiler and the selection results were used as inputs of three different data-driven *** comparison between the models with or without variable selection was *** results showed that the PMI method enhanced the model prediction accuracy and avoided the over-fitting problem.

关键词： NOx emission coal-fired boiler partial mutual information(PMI) data-driven modeling

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Dynamic robust stabilization of fractional-order linear systems with nonlinear uncertain parameters: An LMI approach

arXiv

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arXiv 2019年

作者： Badri, Pouya Sojoodi, Mahdi Zavvari, Elyar Advanced Control Systems Laboratory School of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran

This paper presents a dynamic output feedback controller with determined order for the stabilization of a class of fractional-order system with nonlinear uncertain parameters with fractional order 0 Copyright © 2... 详细信息

关键词： Linear matrix inequalities

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Consensus of fractional-order multi-agent systems: Matrix inequality approach

arXiv

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arXiv 2019年

作者： Zavary, Elyar Sojoodi, Mahdi Advanced Control Systems Laboratory School of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran

This paper investigates a decentralized dynamic output feedback controller for the robust consensus of fractional-order uncertain multi-agent systems. The procedure is decentralized meaning that each agent can only receive output information from its neighbor agents. By an appropriate state transformation, we reduce the consensus problem to stability one, which leads to a matrix inequality. Additionally, a Homotopy-based method is utilized to solve the resulted matrix inequality and to find the controller’s unknown parameters that guarantee the robust consensus of agents. Finally, an illustrative example on multi-agent permanent magnet synchronous motor system and a numerical example are presented to show the effectiveness of the proposed control approach. Copyright © 2019, The Authors. All rights reserved.

关键词： Multi agent systems

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A DNA Computing Model for the Graph Vertex Coloring Problem Based on a Probe Graph

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engineering 2018年第1期4卷 61-77页

作者： Jin xu Xiaoli Qiang Kai Zhang Cheng Zhang Jing Yang Key Laboratory of High Confidence Software Technologies of Ministry of Education Institute of Software School of Electronics Engineering and Computer SciencePeking University Beijing 100871 China Institute of Novel Computer Science and Intelligent Software Guangzhou University Guangzhou 510006 China School of Computer Science Wuhan University of Science and Technology Wuhan 430081 China School of Control and Computer Engineering North China Electric Power University Beijing 102206 China

The biggest bottleneck in DNA computing is exponential explosion, in which the DNA molecules used as data in information processing grow exponentially with an increase of problem size. To overcome this bottleneck and improve the processing speed, we propose a DNA computing model to solve the graph vertex coloring problem. The main points of the model are as follows： The exponential explosion prob- lem is solved by dividing subgraphs, reducing the vertex colors without losing the solutions, and ordering the vertices in subgraphs; and the bio-operation times are reduced considerably by a designed parallel polymerase chain reaction （PCR） technology that dramatically improves the processing speed. In this arti- cle, a 3-colorable graph with 61 vertices is used to illustrate the capability of the DNA computing model. The experiment showed that not only are all the solutions of the graph found, but also more than 99% of false solutions are deleted when the initial solution space is constructed. The powerful computational capability of the model was based on specific reactions among the large number of nanoscale oligonu- cleotide strands. All these tiny strands are operated by DNA self-assembly and parallel PCR. After thou- sands of accurate PCR operations, the solutions were found by recognizing, splicing, and assembling. We also prove that the searching capability of this model is up to 0（3^59）. By means of an exhaustive search, it would take more than 896 000 years for an electronic computer （5 x 10^14 s-1） to achieve this enormous task. This searching capability is the largest among both the electronic and non-electronic computers that have been developed since the DNA computing model was proposed by Adleman＇s research group in 2002 （with a searching capability of 0（2^20））.

关键词： DNA computing Graph vertex coloring problem Polymerase chain reaction

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CBLNER: A Multi-models Biomedical Named Entity Recognition System Based on Machine Learning 1

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15th International Conference on Intelligent Computing, ICIC 2019

作者： Lejun, Gong Xiaolin, Liu Xuemin, Yang Lipeng, Zhang Yao, Jia Ronggen, Yang Jiangsu Key Lab of Big Data Security and Intelligent Processing School of Computer Science Nanjing University of Posts and Telecommunications Nanjing210023 China Faculty Intelligent Science and Control Engineering Jinling Institute of Technology Nanjing211169 China

ISBN: (数字)9783030269692

ISBN: (纸本)9783030269685

Biomedical named entities is fundamental recognition task in biomedical text mining. This paper developed a system for identifying biomedical entities with four models including CRF, LSTM, Bi-LSTM and BiLSTM-CRF. The system achieved the following performance in test data Genia V3.02: CRF with an F score of 75.91%, LSTM with an F score of 71.69%, BiLSTM with a F score of 74.37%, BiLSTM-CRF with a F score of 76.81%. Experimental results show the performance of BiLSTM-CRF model is better than other three models. Compared with CRF model, Bi-LSTM-CRF model has better recognition effect for biological entities in long text and entities that modified by modifiers. Therefore, CBLNER system lays a foundation for further relationship and event extraction, and could also provide reference for entity recognition research in other fields. © 2019, Springer Nature Switzerland AG.

关键词： Character recognition

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An improved approach for automatic spine canal segmentation using probabilistic boosting tree (PBT) with fuzzy support vector machine

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Journal of Ambient Intelligence and Humanized Computing 2020年第6期12卷 6527-6536页

作者： Viji, C. Rajkumar, N. Suganthi, S. T. Venkatachalam, K. kumar, T. Rajesh Pandiyan, Sanjeevi Department of CSE Akshaya College of Engineering and Technology Coimbatore India Department of Computer Engineering Lebanese French University Erbil Iraq School of CSE VIT University Bhopal Bhopal India Department of Information Technology Sri Krishna College of Technology Kovaipudur India Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi China

Spine canal segmentation is an emerging zone in research proposed to help interpretation and processing of advanced MRI and CT images. For instance, high resolution three-dimensional volumes can be divided to provide an estimation of spine canal atrophy. Spine canal segmentation is complex because of assortment of MRI contrasts and variation in human life structures. This investigation illustrates the details of spine canal segmentation techniques and gives a few measurements that can be utilized to contrast with other segmentation strategies. The details of background and foreground subtraction techniques, spine canal segmentation approach and optimization approach which are utilized in the different applications have been considered. In this paper, spine canal segmentation on probabilistic booting tree (PBT) with fuzzy support vector machine performance measures and metrics are analysed in state-of-the art technologies. Proposed approach is performed on the base of the automatic spine canal segmentation with the group of data MR. This proposed segmentation continue with fuzzy support vector machine (FSVM) technique to make fully automatic stream pipeline. The declaration in an automatic segmentation of stream pipeline was implemented with flexible voxel wise classification accompanying dimensions analogous with 3D Haar and labelled machine learning algorithms i.e. probabilistic boosting tree combined fuzzy support vector machine (PBT-FSVM). The novel segmentation technique correlated with MR data sets provides better accuracy than the exiting techniques and it is shown in experimental outcomes. To still improve performance of the results, online learning classification method can be in the proposed work.

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OER: Six Perspectives on Global Misconceptions and Challenges

OER: Six Perspectives on Global Misconceptions and Challenge...

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2019 IEEE International Conference on engineering, Technology and Education, TALE 2019

作者： Towey, Dave Reisman, Sorel Chan, Henry Demartini, Claudio Tovar, Edmundo Margaria, Tiziana University of Nottingham Ningbo China School of Computer Science Ningbo China California State University Fullerton Department of Information Systems and Decision Sciences Fullerton United States Hong Kong Polytechnic University Department of Computing Hong Kong Hong Kong Politecnico di Torino Control Computer Engineering Department Turin Italy Universidad Politécnica de Madrid School of Computer Engineers Madrid Spain University of Limerick Department of Computer Science and Information Systems Limerick Ireland

ISBN: (纸本)9781728126654

Open Educational Resources (OERs) are freely accessible materials for teaching, learning, and research that have been made available such that they can be freely used, modified, and shared. Prompted by the potential positive impact that OERs can have, a growing community of OER enthusiasts has been advocating for their adoption in higher education, and elsewhere. The growing demand for computer science education and training (especially in areas related to artificial intelligence, machine learning, and big data) has led to speculation as to how OERs may be best leveraged to support such teaching and learning. The recent occasion of an international OER workshop at the 2019 IEEE Conference on computers, Software and Applications (COMPSAC) allowed for six OER enthusiasts, all with extensive OER experience, to reflect on the status of OER adoption and understanding. These reflections, addressing misconceptions and challenges, form the basis for this paper. © 2019 IEEE.

关键词： Application programs

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Push-Pull Finite-Time Convergence Distributed Optimization Algorithm

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American Journal of Computational Mathematics 2020年第1期10卷 118-146页

作者： Xiaobiao Chen Kaixin Yan Yu Gao Xuefeng Xu Kang Yan Jing Wang Department of Science Taiyuan University of Technology Taiyuan China Department of Automation Taiyuan University of Technology Taiyuan China Department of Automation School of Control and Computer Engineering North China Electric Power University Beijing China Department of Economics and Management Taiyuan University of Technology Taiyuan China Department of Mechanical and Electrical Engineering Shanxi Energy Institute Taiyuan China School of Medicine Clinical Medicine Datong University Datong China

With the widespread application of distributed systems, many problems need to be solved urgently. How to design distributed optimization strategies has become a research hotspot. This article focuses on the solution rate of the distributed convex optimization algorithm. Each agent in the network has its own convex cost function. We consider a gradient-based distributed method and use a push-pull gradient algorithm to minimize the total cost function. Inspired by the current multi-agent consensus cooperation protocol for distributed convex optimization algorithm, a distributed convex optimization algorithm with finite time convergence is proposed and studied. In the end, based on a fixed undirected distributed network topology, a fast convergent distributed cooperative learning method based on a linear parameterized neural network is proposed, which is different from the existing distributed convex optimization algorithms that can achieve exponential convergence. The algorithm can achieve finite-time convergence. The convergence of the algorithm can be guaranteed by the Lyapunov method. The corresponding simulation examples also show the effectiveness of the algorithm intuitively. Compared with other algorithms, this algorithm is competitive.

关键词： Distributed Optimization Finite Time Convergence Linear Parameterized Neural Network Push-Pull Algorithm Undirected Graph

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