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International Conference on control and Automation (ICCA)

作者： Xia Jiang Xianlin Zeng Jian Sun Jie Chen Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China Beijing Advanced Innovation Center for Intelligent Robots and Systems (Beijing Institute of Technology) Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Ministry of Education Beijing China School of Electronic and Information Engineering Tongji University Shanghai China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

This paper presents a hybrid protocol design for distributed non-differentiable extended monotropic optimization problems, which have various applications in large-scale optimization and evolutionary computation. The considered objective function is the sum of local non-differentiable objective functions, which are assigned to different agents in multi-agent networks, with local set constraints and affine equality constraints. Each agent can only access to its local non-differentiable objective function, local set constraint and equality constraint, and exchange information with its neighbors to obtain the global optimal solution. For this type of optimization problems, we propose a distributed state-dependent hybrid method over multi-agent networks. In addition, we properly design the jump map and jump set to improve the transient performance and accelerate the consensus process of existing distributed continuous-time methods. With invariance principle of hybrid dynamical systems, we prove that the proposed hybrid protocol converges to the global optimal solution. We verify that the proposed hybrid method has a good convergence property and transient performance through numerical experiments.

关键词： Optimization Protocols Linear programming Dynamical systems Heuristic algorithms Convergence Transient analysis

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An Adaptive Disturbance Rejection controller for Artificial Pancreas

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IFAC-PapersOnLine 2020年第2期53卷 16372-16379页

作者： Deheng Cai Wei Liu Eyal Dassau Francis J. Doyle Iii Xiaoling Cai Junzheng Wang Linong Ji Dawei Shi State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing 100081 China Department of Endocrine and Metabolism Peking University People’s Hospital Beijing China. Harvard John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge MA 02138 USA.

Artificial pancreas (AP) systems are designed to automate glucose management for patients with type 1 diabetes. In this work, we propose an adaptive disturbance rejection control approach for AP systems to achieve safe and effective glucose regulation. The controller is built within the framework of active disturbance rejection control, but incorporates safety operation constraints, and glucose- and velocity-dependent parameter adaptation modules for the key control parameters. In silico performance comparison between the proposed controller and an adaptive zone model predictive controller (MPC) (Shi, Dassau, and Doyle III, 2019a) is conducted on the 10-adult cohort of the FDA-accepted UVA/Padova T1DM simulator. For both announced and unannounced meals, the controller achieves comparable glucose regulation performance in terms of mean glucose (134.9 mg/dL vs. 135.4 mg/dL, p < 0.001; 149.7 mg/dL vs. 151.7 mg/dL, p < 0.001, respectively) and percentage time in [70, 180] mg/dL (93.8% vs. 92.4%, p < 0.001; 76.0% vs. 72.4%, p < 0.001, respectively) without increasing the risk of hypoglycemia. The results indicate the feasibility of achieving comparable glucose regulation performance through a non-optimization control law for AP systems.

关键词： Artificial pancreas Active disturbance rejection control Adaptive control Glucose regulation

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Mobile Energy Transfer in Internet of Things

arXiv

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arXiv 2020年

作者： Zhang, Qingqing Wang, Gang Giannakis, Georgios B. Liu, Qingwen Chen, Jie College of Electronic and Information Engineering Tongji University Shanghai201800 China Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN 55455 United States State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Tongji University Shanghai200092 China

—Internet of things (IoT) is powering up smart cities by connecting all kinds of electronic devices. The power supply problem of IoT devices constitutes a major challenge in current IoT development, due to the poor battery endurance as well as the troublesome cable deployment. The wireless power transfer (WPT) technology has recently emerged as a promising solution. Yet, existing WPT advances cannot support free and mobile charging like Wi-Fi communications. To this end, the concept of mobile energy transfer (MET) is proposed, which relies critically on an resonant beam charging (RBC) technology. The adaptive (A) RBC technology builds on RBC, but aims at improving the charging efficiency by charging devices at device preferred current and voltage levels adaptively. A mobile ARBC scheme is developed relying on an adaptive source power control. Extensive numerical simulations using a 1,000mAh Li-ion battery show that the mobile ARBC outperforms simple charging schemes such as the constant power charging, the profile-adaptive charging, and the distance-adaptive charging in saving energy. Copyright © 2020, The Authors. All rights reserved.

关键词： Energy transfer

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Non-fragile finite-time dissipative piecewise control for time-varying system with time-varying delay

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IET control Theory & Applications 2019年第3期13卷 321-332页

作者： Menghua Chen Jian Sun School of Automation Beijing Institute of Technology Beijing 100081 People's Republic of China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 People's Republic of China

This study is concerned with the problem of non-fragile finite-time dissipative (FTD) control for time-varying system with delay. The delay is time varying and belongs to a given interval. Finite-time bounded (FTB) and FTD concepts are introduced to time-varying system with delay. First, new FTB conditions are derived for time-varying system with delay by using a piecewise Lyapunov functional combined with reciprocally convex approach. Second, FTD conditions are obtained to guarantee that the time-varying system with delay is not only FTB but also satisfies a dissipative performance index. Moreover, based on the FTD conditions, the non-fragile piecewise feedback controllers are designed in terms of linear matrix inequalities (LMIs). In addition, an LMI-based iterative algorithm is given to obtain the piecewise feedback non-fragile controller gains. Finally, numerical examples demonstrate the effectiveness of the proposed method.

关键词： linear matrix inequalities delays feedback iterative methods control system synthesis Lyapunov methods time-varying systems performance index finite-time dissipative control time-varying system nonfragile piecewise feedback controllers piecewise feedback nonfragile controller gains time-varying delay nonfragile finite-time dissipative piecewise control finite-time bounded piecewise Lyapunov functional reciprocally convex approach dissipative performance index linear matrix inequalities LMI-based iterative algorithm

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Exponential input-to-state stability of impulsive stochastic fuzzy Cohen-Grossberg neural networks with distributed infinite transmission delays

Exponential input-to-state stability of impulsive stochastic...

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第三十八届中国控制会议

作者： Weisong Zhou Dan Shi Wei Zhu Key Lab of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications

In this paper, we study a class of impulsive stochastic fuzzy delayed Cohen-Grossberg neural networks with distributed infinite transmission delays. By Razumikhin technique and differential inequalities, some sufficient conditions ensuring the mean-square exponential input-to-state stability of our considered Cohen-Grossberg neural networks are obtained. These results can include constant delay and bounded distributed delay as its special cases, and generalize and improve some earlier publications. A numerical example is demonstrated to verify the theoretical results.

关键词： Impulsive Stochastic Infinite delays Cohen-Grossberg neural networks Exponential input-to-state stability

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Adaptive Neural Network control for a Lower-Limb Exoskeleton using Variable Stiffness Transferring

Adaptive Neural Network Control for a Lower-Limb Exoskeleton...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Longbin Zhang Yingbai Hu Hang Su Jiehao Li Salih Ertug Ovur KTH MoveAbility Lab and KTH BioMEx Center KTH Royal Institute of Technology Stockholm Sweden Technical University of Munich Munich Germany Politecnico di Milano Milano Italy State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

ISBN: (数字)9781728164793

ISBN: (纸本)9781728164809

Lower-limb exoskeletons are increasingly used in gait assistance applications to assist patients with locomotive disorders in rehabilitation and daily life. To provide assistance based on the user's variable joint stiffness with human-like characteristics is a growing and challenging field. This paper proposed an adaptive controller for a lower-limb exoskeleton with time-varying delay using variable stiffness transferring strategy. Neural network compensation was applied to estimate the nonlinearity caused by the time-varying delay and the model uncertainties in the lower-limb exoskeleton systems. To compensate for the delay, an integral Lyapunov function was introduced and an adaptive Lyapunov-based control structure was constructed. In the controller design, a variable stiffness transferring strategy was integrated and the stiffness was transferred from an able-bodied individual estimated with muscle forces and musclotendinous stiffness. By utilizing the proposed adaptive neural network control strategy and adaptive Lyapunov-based control structure, the global stability of lower-limb exoskeleton system was guaranteed and the tracking errors converged to the zero. The proposed control strategy was validated on 2-DOFs knee and ankle lower limb exoskeleton in simulation, demonstrating effective results in trajectories tracking, and thus is crucial for determining strategies for exoskeleton control.

关键词： Exoskeletons Robots Muscles Adaptive systems Force Mathematical model Mechatronics

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Development of Sheet Palletizing Manipulator Based on Multi-link Mechanism

Research Square

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Research Square 2020年

作者： Chen, Zhihua Wang, Shoukun Liu, Quan Wang, Junzheng Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology School of Automation Beijing Institute of Technology Beijing100081 China New Energy Laboratory College of Mechanical and Electrical Engineering Beijing Information Science and Technology University Beijing100192 China

In view of the disadvantages of Traditional tandem joint type thin-plate palletizing robots using push-down adsorption sorting, such as moving path complexity, large occupied space, joint error stack and low end control precision, a novel multi-link mechanism thin-plate palletizing robot is developed. The kinematics analysis is carried out based on the analysis of the overall structure for the manipulator, a genetic algorithm based on the stroke speed ratio K, the transmission angle γ and the four-bar size is proposed to realize the optimal design of the four-link rocker arm mechanism. Secondly, a finite element based overall structure analysis method is proposed, which obtains the most affected part of the vibration process of a manipulator and performs load verification to prevent early warning and reference of faults caused by mechanical resonance. To solve the control problem of nonlinear strongly coupled dynamic systems, an iterative learning fuzzy adaptive control algorithm is proposed to achieve the smooth running of the manipulator and the high-precision tracking of the end centroid trajectory. The experimental results verify the feasibility and effectiveness of the proposed multi-link controllable thin-plate palletizing manipulator's overall structural design and iterative learning control method, which is well applied in practical engineering. © 2020, CC BY.

关键词： Manipulators

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Graph Optimization Based Long-distance GPS/IMU Integrated Navigation

Graph Optimization Based Long-distance GPS/IMU Integrated Na...

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第三十八届中国控制会议

作者： Xiaojie Gu Fengdi Zhang Jian Xu Qing Yuan Hongwei Ma Xiangdong Liu Zhen Li School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing

The accurate position estimation plays an critical role in the autonomous navigation for Micro Aerial Vehicles(MAV).Global positioning System(GPS) and inertial measurement unit(IMU) are two common sensors for navigation widely used on MAVs in the urban environment. Both of them have its distinct disadvantages that the GPS is susceptible to environmental interference and the IMU has accumulative errors. To overcome these problems, a GPS/IMU integrated system based on the factor graph optimization is developed in this paper. Unlike the conventional extended Kalman filter(EKF)-based method, the graph optimization method takes the whole trajectory into consideration so that it can achieve enough accuracy even after a long distance. Furthermore, the IMU preintegration method is used to avoid the repeated computation of high-rate IMU *** with the EKF method, the experimental results on the Zurich urban micro aerial vehicle dataset show the superior accuracy of the proposed factor graph optimization algorithm.

关键词： Global positioning System(GPS) inertial measurement unit(IMU) IMU preintegration graph optimization integrated navigation

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Preface——Special Issue on New Directions in Nonlinear and Distributed control

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Journal of systems Science & complexity 2018年第1期31卷 1-3页

作者： LIU Tengfei XIN Bin JIANG Zhong-Ping State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang 110819 China School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing 100081 China Tandon School of Engineering New York University Brooklyn NY 11201 USA

Nonlinearity is ubiquitous in engineering and natural *** development of nonlinear control can be traced back to decades *** date,the research has reached the stage that emphasizes developing methodologies that can ha... 详细信息

关键词：控制问题非线性分布式工程应用程序电子物理自然系统生产线相互作用

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An Improved Version of DMOEA-εC for Many-objective Optimization Problems: IDMOEA-εC

An Improved Version of DMOEA-εC for Many-objective Optimiza...

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第三十八届中国控制会议

作者： Juan Li Bin Xin School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology

The decomposition strategy and the ε-constraint method are two important strategies in the field of multi-objective optimization. DMOEA-εC first attempts to incorporate the ε-constraint method into the decomposition strategy and solve a multi-objective optimization problem(MOP) via optimizing a series of scalar constrained subproblems collaboratively with the help of information from neighboring subproblems. However, given the inefficiency of applying DMOEA-εC to deal with many-objective optimization problems(MaOPs), a two-stage upper bound vectors generation procedure is proposed to generate widely spread upper bound vectors in a high-dimensional space. Besides, a boundary points maintenance mechanism is put forward to remedy the diversity loss of a population in DMOEA-εC. Based on the above, DMOEA-εC with the two-stage upper bound vectors generation procedure and the boundary points maintenance mechanism, named as IDMOEA-εC, is presented for MaOPs. IDMOEA-εC is compared with four state-of-the-art many-objective evolutionary algorithms, including HypE, NSGA-Ⅲ, MOEADD, and Two Arch2. Experimental studies demonstrate that IDMOEA-εC outperforms or performs competitively against these algorithms on the majority of sixteen DTLZ test instances with up to 10 objectives.

关键词： Many-objective optimization decomposition ε-constraint method two-stage upper bound vectors generation procedure boundary points maintenance mechanism

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