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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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Stabilizability of Networked control systems via Packet-loss Dependent Output Feedback controllers

Stabilizability of Networked Control Systems via Packet-loss...

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2008 American control Conference (ACC), vol.9

作者： Junyan Yu Long Wang Mei Yu Yingmin Jia Jie Chen Intelligent Control Laboratory Center for Systems and Control College of Engineering Peking University Beijing China Department of Automation North China Electric Power University Beijing China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China

We consider the output feedback stabilizability of networked control systems with bounded packet loss. A packet-loss dependent Lyapunov function is adopted to design packet-loss dependent stabilizing output feedback controllers by resolving some linear matrix inequalities. Moreover, two types of packet-loss processes are discussed: one is the arbitrary packet-loss process, and the other is the Markovian packet-loss process. A numerical example and some simulations are worked out to demonstrate the effectiveness of the proposed design technique.

关键词： Networked control systems Output feedback control systems Switched systems State feedback Lyapunov method Linear matrix inequalities Electrical equipment industry Industrial control Sufficient conditions

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Exponential input-to-state stability of stochastic fuzzy delayed Cohen-Grossberg neural networks under impulsive perturbations

Exponential input-to-state stability of stochastic fuzzy del...

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第37届中国控制会议

作者： Weisong Zhou Hao Zeng Donghai Wu 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 EducationChongqing University of Posts and Telecommunications

In this paper,we study a class of stochastic fuzzy delayed Cohen-Grossberg neural networks under impulsive *** Razumikhin method and iteration technique,some sufficient conditions ensuring the mean-square exponential input-to-state stability of the designed delayed neural networks are *** results can generalize and improve some earlier publications.A numerical example is demonstrated to verify the theoretical results.

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

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IEEE International Conference on Mechatronics and Automation

作者： Ying Wu Qiang Huang Xuechao Chen Zhangguo Yu Libo Meng Gan Ma Peisen Zhang Weimin Zhang Intelligent Robotics Institute Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing China International Joint Research Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing China

ISBN: (纸本)9781479970995

This paper introduces the similarity evaluation on humanoid facial expression. For the purpose of understanding easily, firstly, the process of designing humanoid robot's facial expressions is explored in brief. Then, a similarity function is proposed to evaluate the similarity of the robot facial motion compared with the human being quantitatively based on both the kinematics and dynamics factors, also including how to select the key value of parameter in similarity function. Finally, the effectiveness of the similarity function is confirmed by an experiment of facial expressions based on BHR-4 robot.

关键词： Joints Kinematics Dynamics Trajectory Humanoid robots Rhythm

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Adaptive sliding mode control of electromechanical actuator with improved parameter estimation

Adaptive sliding mode control of electromechanical actuator ...

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Asian control Conference

作者： Hao Li Yongqiang Bai Zhong Su School of Automation Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

An adaptive sliding mode control scheme for electromechanical actuator has been presented. The adaptive control strategy can estimate the uncertain parameters and adaptively compensate the modeled dynamical uncertainties, while the sliding mode control method overcomes the unmodelled dynamics. In the adaptive law an equivalent output injection of the sliding mode observer which contains the parameter estimation error is used, and estimates of parameters can approximate the true values without prediction-error that is typically used in compositive adaptive law. Due to the improved estimation of uncertain parameters, the sliding mode law can robustifies the design against model uncertainties with a small swithcing gain. Stability of the system with the proposed approach has been proved and it has also been shown that the system states can reach the sliding mode in finite time. Finally, the effectiveness of the proposed control scheme has been exhibited via simulation examples.

关键词： Parameter estimation Sliding mode control Actuators Aerodynamics Robustness Adaptive control Uncertainty

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Unsupervised Learning of Gaussian Mixture Model with Application to Image Segmentation

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Chinese Journal of Electronics 2023年第3期19卷 451-456页

作者： Bo Li Wenju Liu Lihua Dou School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling. Finite Gaussian mixture model is usually used in practice and the selection of number of mixture components is a significant problem in its application. For example, in image segmentation, it is the donation of the number of segmentation regions. The determination of the optimal model order therefore is a problem that achieves widely attention. This paper proposes a degenerating model algorithm that could simultaneously select the optimal number of mixture components and estimate the parameters for Gaussian mixture model. Unlike traditional model order selection method, it does not need to select the optimal number of components from a set of candidate models. Based on the investigation on the property of the elliptically contoured distributions of generalized multivariate analysis, it select the correct model order in a different way that needs less operation times and less sensitive to the initial value of EM. The experimental results show the effectiveness of the algorithm.

关键词： Training Image segmentation Analytical models Parameter estimation Estimation Probability density function Speech processing

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Real-time terrain assessment and Bayesian-based path planning for off-road navigation

Real-time terrain assessment and Bayesian-based path plannin...

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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Tianwei Niu Shuwei Yu Liang Wang Haoyu Yuan Shoukun Wang Junzheng Wang Localization and Motion Planning School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System School of Automation Beijing Institute of Technology Beijing China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In the context of unstructured and unknown environment, the autonomous navigation still faces many challenges, such as assessing rough terrain and deciding how to safely navigate complex terrain. In this work, we propose a robust and practical off-road navigation framework that has been successfully deployed on a vibroseis truck for land exploration. First, in degraded wild scenes, a tightly coupled lidar-GNSS-inertial fusion odometry and mapping framework is adopted to construct a local point cloud map around the vehicle in real-time and provide precise localization. Then, based on amplitude-frequency characteristic analysis and point cloud PCA, a multi-layer terrain assessment map containing terrain roughness, obstacles and slope information is obtained. Finally, combining Gaussian distribution based adaptive sampler and Bayesian sequentially updated proposal distribution, a local graph is efficiently built to obtain multiple path solutions under constrained conditions. Both simulations and field experiments show that the proposed navigation framework can decide how to travel on a flat road even in harsh terrain conditions, naturally suppressing frequent attitude angle changes and preventing vehicle accidents.

关键词： Point cloud compression Location awareness Adaptation models Navigation Roads Gaussian distribution Real-time systems Bayes methods Proposals Principal component analysis

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A new flexible controller for a humanoid robot that considers visual and force information interaction

A new flexible controller for a humanoid robot that consider...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Gan Ma Qiang Huang Zhangguo Yu Xuechao Chen Weimin Zhang Junyao Gao Libo Meng Yun-Hui Liu IRI Beijing Institute of Technology Beijing China Ministry of Education Key Laboratory of Biomimetic Robots and Systems China Beijing Institute of Technology Beijing Beijing CN Key Laboratory of Intelligent Control and Decision of Complex System China

To enhance the safety of a humanoid robot when it is operating a complex environment, a number of methods that combine visual and force information have been presented. These methods are generally divided into two approaches. The first approach is to coordinate the visual controller and force controller in a parallel way, and the second approach is to coordinate them in series. However, these two approaches do not consider the interaction between the visual controller and force controller. Specifically, the first approach does not consider the interaction between the controllers. The second approach only considers the effect of the output of the visual controller on the force controller, while the effect of the force controller on the visual controller is not considered. This study presents a design for a new flexible controller for a humanoid robot that considers the interaction of visual and force information. The advantages of the proposed method are that it simultaneously incorporates the functions of a visual servo controller and a flexible controller as well as its ability to consider the interaction of visual and force information when a humanoid robot is operating.

关键词： Robot kinematics Visualization Force Cameras Humanoid robots Robot vision systems

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Research on Path Planning of Mobile Robot Based on DWA-IMP-A* Algorithm

Research on Path Planning of Mobile Robot Based on DWA-IMP-A...

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Chinese control Conference (CCC)

作者： Zhi Liu Lin Zhang Shoukun Wang Tianwei Niu Yongkang Xu Jin Cao Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology School of Automation Beijing Institute of Technology Beijing China

Path planning is one of the most critical links in mobile robots. Its timeliness, security and accessibility are crucial to the development and wide application of mobile robots. However, in solving the problem of path planning, the most popular A* algorithm has some problems, such as heuristic function cannot be estimated accurately, node redundancy, path is not smooth, and obstacle avoidance cannot be achieved in real time. To solve these problems, A fusion algorithm of improved A* combined with reverse path and dynamic window method (DWA-IMP-A*) was proposed. The algorithm refines the heuristic function by incorporating the reverse path. The node optimization algorithm is used to further reduce the path length. The generated trajectories are smoothed by cubic spline interpolation. At the same time, it is integrated with the improved DWA algorithm to improve the efficiency and safety of robot path planning. The algorithm takes ROS mobile robot as the carrier and is tested under typical road conditions. Compared with A* algorithm, the planning time is reduced by 54.6% and the path length is reduced by 6.37%. Experimental results verify the effectiveness and robustness of the algorithm. The research results have certain reference significance for the path planning of various types of mobile robots and the research of driverless vehicles.

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Transfer function of fluidic system in liquid-circular angular accelerometer

Transfer function of fluidic system in liquid-circular angul...

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IEEE Instrumentation and Measurement Technology Conference

作者： Siyuan Cheng Meiling Wang Xiang Li Meifeng Xiao Mengyin Fu Xin Zheng Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Beijing China Nanjing University of Science and Technology Nanjing China The Third Academic of Aerospace and Technology Group of China Beijing China

ISBN: (纸本)9781467392211

In this paper, a new kind of liquid-circular angular accelerometer is studied. Based on electrokinetic phenomenon, this angular accelerometer is designed with a porous transducer and fluid mass. Due to the existence of electrical double layer between transducer and fluid mass, this angular accelerometer is able to convert angular acceleration input to electrical signal. The whole system is composed of fluidic system and molecular electronic system. Theoretical analysis and several experiments are implemented to obtain transfer function model of fluidic system. The flow in transducer satisfies the Darcy Law in the experiment and angular velocity input is proved to have no effect on the output. A prototype is designed to compare the output of theoretical model and experiments. All of the experiments prove that the fluidic system of this liquid-circular angular accelerometer can be seen as a first-order system, especially when the frequency of input is less than 30Hz and its transfer function is derived.

关键词： Transducers Fluids Prototypes Accelerometers Transfer functions Electron tubes Acceleration

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