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Performance analysis of fuzzy BlS using different cluster methods for classification

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Science china(Information Sciences) 2021年第4期64卷 232-234页

作者： Shuang FENG c.l.philip chen School of Applied Mathematics Beijing Normal University Faculty of Science and Technology University of Macau

Dear editor,Neural networks (NNs) and fuzzy systems are commonly used computational intelligence techniques, each with their own merits in terms of applications. The integration of NNs and fuzzy systems, which leads to a hybrid framework known as neuro-fuzzy systems, inherits the useful properties of its constituents:the learning power of an NN and the knowledge representation of a fuzzy inference system,

关键词： fuzzy broad learning system clustering fuzzy c-means classification TSK fuzzy system

Discriminative graph regularized broad learning system for image recognition

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Science china(Information Sciences) 2018年第11期61卷 179-192页

作者： Junwei JIN Zhulin lIU c.l.philip chen Faculty of Science and Technology University of Macau Dalian Maritime University State Key laboratory of Management and control for complex Systems Institute of AutomationChinese Academy of Sciences

Broad learning system(BlS) has been proposed as an alternative method of deep learning. The architecture of BlS is that the input is randomly mapped into series of feature spaces which form the feature nodes, and the output of the feature nodes are expanded broadly to form the enhancement nodes, and then the output weights of the network can be determined analytically. The most advantage of BlS is that it can be learned incrementally without a retraining process when there comes new input data or neural nodes. It has been proven that BlS can overcome the inadequacies caused by training a large number of parameters in gradient-based deep learning algorithms. In this paper, a novel variant graph regularized broad learning system(GBlS) is proposed. Taking account of the locally invariant property of data, which means the similar images may share similar properties, the manifold learning is incorporated into the objective function of the standard BlS. In GBlS, the output weights are constrained to learn more discriminative information,and the classification ability can be further enhanced. Several experiments are carried out to verify that our proposed GBlS model can outperform the standard BlS. What is more, the GBlS also performs better compared with other state-of-the-art image recognition methods in several image databases.

关键词： broad learning system deep learning graph regularization image recognition feature extraction incremental learning

A Survey of Human-centered Intelligent Robots:Issues and challenges

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IEEE/cAA Journal of Automatica Sinica 2017年第4期4卷 602-609页

作者： Wei He Zhijun li c.l.philip chen IEEE School of Automation and Electrical Engineering University of Science and Technology Beijing college of Automation Science and Engineering South China University of Technology Department of computer and Information Science Faculty of Science and Technology University of Macao

Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important research field that spans all of the robot capabilities including navigation, intelligent control, pattern recognition and human-robot interaction. This paper focuses on the recent achievements and presents a survey of existing works on human-centered robots. Furthermore, we provide a comprehensive survey of the recent development of the human-centered intelligent robot and discuss the issues and challenges in the field.

关键词： Human-centered robots human-robot interaction intelligent control navigation path planning pattern recognition

Integral Barrier lyapunov function-based adaptive control for switched nonlinear systems

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Science china(Information Sciences) 2020年第3期63卷 212-225页

作者： lei lIU Yan-Jun lIU Aiqing chen Shaocheng TONG c.l.philip chen college of Science Liaoning University of Technology computer Science and Engineering South China University of Technology Navigation college Dalian Maritime University

This paper presents an adaptive control method for a class of uncertain strict-feedback switched nonlinear systems. First, we consider the constraint characteristics in the switched nonlinear systems to ensure that all states in switched systems do not violate the constraint ranges. Second, we design the controller based on the backstepping technique, while integral Barrier lyapunov functions(i BlFs) are adopted to solve the full state constraint problems in each step in order to realize the direct constraints on state ***, we introduce the lyapunov stability theory to demonstrate that the adaptive controller achieves the desired control goals. Finally, we perform a numerical simulation, which further verifies the significance and feasibility of the presented control scheme.

关键词： adaptive control switched nonlinear systems integral Barrier lyapunov functions backstepping technique full state constraints

Boosting Adaptive Weighted Broad learning System for Multi-label learning

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IEEE/cAA Journal of Automatica Sinica 2024年第11期11卷 2204-2219页

作者： Yuanxin lin Zhiwen Yu Kaixiang Yang Ziwei Fan c.l.philip chen the School of computer Science and Engineering in South china University of Technology IEEE the Pengcheng laboratory

Multi-label classification is a challenging problem that has attracted significant attention from researchers, particularly in the domain of image and text attribute annotation. However, multi-label datasets are prone to serious intra-class and inter-class imbalance problems, which can significantly degrade the classification performance. To address the above issues, we propose the multi-label weighted broad learning system(MlW-BlS) from the perspective of label imbalance weighting and label correlation mining. Further, we propose the multi-label adaptive weighted broad learning system(MlAW-BlS) to adaptively adjust the specific weights and values of labels of MlW-BlS and construct an efficient imbalanced classifier set. Extensive experiments are conducted on various datasets to evaluate the effectiveness of the proposed model, and the results demonstrate its superiority over other advanced approaches.

关键词： Broad learning system label correlation mining label imbalance weighting multi-label imbalance

Dynamic Event-Triggered consensus control for Input constrained Multi-Agent Systems With a Designable Minimum Inter-Event Time

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IEEE/cAA Journal of Automatica Sinica 2024年第3期11卷 649-660页

作者： Meilin li Yue long Tieshan li Hongjing liang c.l.philip chen the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China IEEE the Yangtze Delta Region Institute University of Electronic Science and Technology of ChinaHuzhou 313000 the laboratory of Electromagnetic Space cognition and Intelligent control Beijing 100089China the School of computer Science and Engineering South China University of TechnologyGuangzhou 510006

This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first ***,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale *** is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event *** addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable ***,the results are extended to regional consensus of the MASs with the bounded control *** simulations show the effectiveness of the proposed approach.

关键词： constrained input designable minimum inter-event time directed communication topology dynamic event-triggered mechanism MASs consensus control

containment control of multi-agent systems with nonvanishing disturbance via topology reconfiguration

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Science china(Information Sciences) 2021年第7期64卷 250-252页

作者： Qihe SHAN Fei TENG Tieshan lI c.l.philip chen Navigation college Dalian Maritime University college of Information Science and Engineering Northeastern University

Dear editor,Multi-agent systems (MASs) are ubiquitous in natural as well as artificial systems. Over the past several decades, an increasing number of researchers have devoted attention to distributed cooperative cont... 详细信息

关键词： multi agent nonvanishing disturbance topology reconfiguration containment control convex parameters

Formation control with obstacle avoidance of second-order multi-agent systems under directed communication topology

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Science china(Information Sciences) 2019年第9期62卷 144-157页

作者： Guoxing WEN c.l.philip chen Hui DOU Hongli YANG chunfang lIU college of Science Binzhou University Department of computer and Information Science Faculty of Science and Technology University of Macau college of Navigation Dalian Maritime University State Key laboratory of Management and control for complex Systems Institute of AutomationChinese Academy of Sciences Mathematics and Systems Science college Shandong University of Science and Technology

This paper addresses the obstacle avoidance problem of formation control for the multi-agent systems modeled by double integrator dynamics under a directed interconnection topology. The control task is finished by a leader-follower formation scheme combined with an artificial potential field(APF) *** leader-follower scheme is carried out by taking the desired trajectory with the desired velocity as virtual leader, while the APF method is carried out by dealing with the obstacles as the high potential points. When the obstacle avoidance tasks are finished, the artificial potential forces degrade the formation performance, so their undesired effects are treated as disturbances, which is analyzed by the robust H∞performance. Based on lyapunov stability theory, it is proved that the proposed formation approach can realize the control objective. The result is also extended to the switching multi-agent formation. The effectiveness of the proposed formation scheme is further confirmed by simulation studies.

关键词： formation control obstacle avoidance artificial potential field method H_∞ performance second-order multi-agent system directed topology

Adaptive control of MIMO Mechanical Systems with Unknown Actuator Nonlinearities Based on the Nussbaum Gain Approach

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IEEE/cAA Journal of Automatica Sinica 2016年第1期3卷 26-34页

作者： ci chen Zhi liu Yun Zhang c.l.philip chen Shengli Xie School of Automation Guangdong University of Technology IEEE Faculty of Science and Technology University of Macao Guangdong Key laboratory of IoT Information Processing

This paper investigates MIMO mechanical systems with unknown actuator nonlinearities. A novel Nussbaum analysis tool for MIMO systems is established such that unknown time-varying control coefficients are tackled. In contrast to existing literatures on continuous-time systems, the newly-developed Nussbaum tool focuses on extending the traditional Nussbaum result from one dimensional case to the multiple one. Specifically, not only the multiple unknown input coefficients are extended to the time-varying, but also the limitation of the prior knowledge of coefficients' upper and lower bounds is removed. Furthermore, an adaptive robust controller associated with the proposed tool is presented. The asymptotic tracking of MIMO mechanical systems is guaranteed with the help of the lyapunov Theorem. Finally, a simulation example is provided to examine the validity of the proposed scheme. © 2014 chinese Association of Automation.

关键词： Actuators Adaptive control systems control nonlinearities Mechanical actuators Mechanics MIMO systems Time varying control systems