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Distributed swarm control for multi-robot systems inspired by shepherding behaviors

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Science China(Technological Sciences) 2024年第7期67卷 2191-2202页

作者： SUN guiBin gu haibo LÜJinHu School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Zhongguancun Laboratory Beijing 100094China

Swarming behaviors play an eminent role in both biological and engineering research, and show great potential applications in many emerging fields. Traditional swarming models still lack integrity, uniformity, and stability in swarm forming processes,resulting in fragmentation and void phenomena. Inspired by the shepherding behaviors observed in nature, we propose an integrated negotiation-control scheme for distributed swarm control of massive robots. The core idea of this scheme is that the robots at the boundary of the group herd the internal robots to form an equilibrium swarm. For this purpose, we introduce a concept of virtual group center towards which boundary robots herd internal robots. Then, a distributed negotiation mechanism is designed to allow each robot to negotiate the virtual group center only through local interactions with its neighbors. After that, we propose a shepherding-inspired swarm control law to drive a group of robots to form an integrated, uniform, and stable configuration from any initial states. Both numerical and flight simulations are presented to verify the effectiveness of our proposed swarm control scheme.

关键词： swarm control multi-robot system negotiation-control scheme shepherding behavior

Synchronization for Competitive Neural Networks by Output Feedback and Impulsive Control

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Synchronization for Competitive Neural Networks by Output Fe...

An overview on the designs of distributed observers in LTI multi-agent systems

第25届中国控制与决策会议

作者： haibo gu haibo Lu College of Mathematics Sciences Xinjiang Normal University

ISBN: (纸本)9781467355339

In this paper, a linear static output feedback impulsive control law is designed to achieve globally exponential synchronization of coupled delayed competitive neural networks with different time scales. By using Lyapunov functional method and mathematical induction method, some sufficient conditions for globally exponential synchronization of coupled neural networks via output feedback impulsive control are established. With the help of LMI solvers, a linear output feedback impulsive controllers can be obtained easily. An example with numerical simulation is given to demonstrate the effectiveness of the theory results.

关键词： Competitive neural networks Impulsive control Synchronization LMI method.

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Science China(Technological Sciences) 2021年第11期64卷 2337-2346页

作者： PEI YingQing gu haibo LIU KeXin LU JinHu Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain ComputingBeihang UniversityBeijing 100191China

With the rapid development of information technologies and cloud computing, sensor networks play an increasingly important role in our society. Over the past few decades, distributed observer theory has attracted unprecedented attention due to its wide potential applications in different areas. Meanwhile, various approaches and algorithms have been proposed and investigated. The design of distributed observers is one of the frontier topics of system and control research, which has the significant theoretical values and broad application prospects. This paper attempts to review the representative models and the corresponding approaches for distributed observer design in linear time-invariant(LTI) systems. Firstly, the research backgrounds and main advances of distributed observer designs are briefly reviewed. Then, recent results of distributed observer designs for discrete-time and continuous-time LTI multi-agent systems(MASs) are introduced in detail, respectively. Finally, the prospects and the future work directions of the design of distributed observers are put forward. The main purpose of this paper is to promote the emerging topic on the designs of distributed observers, with focuses on the interdisciplinary interest from technological sciences.

关键词： multi-agent system linear time-invarient system distributed observer consensus

Neural-network-based fully distributed formation control for nonlinear multi-agent systems with event-triggered communication

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Science China(Technological Sciences) 2024年第1期67卷 209-220页

作者： ZHU guoLiang LIU KeXin gu haibo LÜJinHu School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Zhongguancun Laboratory Beijing 100094China

This paper investigates the consensus-based formation control problem for multi-agent systems with unknown nonlinear *** achieve the desired formation,we propose two formation controllers to achieve the desired formation,one based on system states and the other on system *** proposed controllers utilize adaptive gains to avoid global information and neural networks to estimate and compensate for *** proposed event-triggered schemes avoid continuous communication among agents and exclude the Zeno *** analysis reveals that formation errors are bounded,and numerical simulations are used to validate the effectiveness of the proposed approaches.

关键词： formation control neural network adaptive control event-triggered communication multi-agent systems

同方期刊数据库

Identifying topologies and system parameters of uncertaintime-varying delayed complex networks

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Science China(Technological Sciences) 2019年第1期62卷 94-105页

作者： WANG Xiong gu haibo WANG QianYao Lü JinHu LSC Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment and Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

Node dynamics and network topologies play vital roles in determining the network features and network dynamical *** it is of great theoretical significance and practical value to recover the topology structures and system parameters of uncertain complex networks with available information. This paper presents an adaptive anticipatory synchronization-based approach to identify the unknown system parameters and network topological structures of uncertain time-varying delayed complex networks in the presence of noise. Moreover, during the identification process, our proposed scheme guarantees anticipatory synchronization between the uncertain drive and constructed auxiliary response network simultaneously. Particularly, our method can be extended to several special cases. Furthermore, numerical simulations are provided to verify the effectiveness and applicability of our method for reconstructing network topologies and node parameters. We hope our method can provide basic insight into future research on addressing reconstruction issues of uncertain realistic and large-scale complex networks.

关键词： system parameters and network topologies identification anticipatory synchronization uncertain time-varying delayed complex networks noise-perturbed complex networks

A Modified Ant Colony Optimization Algorithm for Tumor Marker Gene Selection

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Genomics, Proteomics & Bioinformatics 2009年第4期7卷 200-208页

作者： Hualong Yu guochang gu haibo Liu Jing Shen Jing Zhao College of Computer Science and Technology Harbin Engineering University Harbin 150001 China.

Microarray data are often extremely asymmetric in dimensionality, such as thousands or even tens of thousands of genes but only a few hundreds of samples or less. Such extreme asymmetry between the dimensionality of genes and samples can lead to inaccurate diagnosis of disease in clinic. Therefore, it has been shown that selecting a small set of marker genes can lead to improved classification accuracy. In this paper, a simple modified ant colony optimization （ACO） algorithm is proposed to select tumorelated marker genes, and support vector machine （SVM） is used as classifier to evaluate the performance of the extracted gene subset. Experimental results on several benchmark tumor microarray datasets showed that the proposed approach produces better recognition with fewer marker genes than many other methods. It has been demonstrated that the modified ACO is a useful tool for selecting marker genes and mining high dimension data

关键词： microarray data ant colony optimization marker gene selection support vector machine

Razumikhin-Type Theorems on p-th Moment Stability for Stochastic Switching Nonlinear Systems with Delay

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Journal of Applied Mathematics and Physics 2016年第7期4卷 1237-1244页

作者： haibo gu Caixia Gao School of Mathematical Sciences Inner Mongolia University Hohhot China

This paper mainly tends to utilize Razumikhin-type theorems to investigate p-th moment stability for a class of stochastic switching nonlinear systems with delay. Based on the Lyapunov-Razumik- hin methods, some sufficient conditions are derived to check the stability of stochastic switching nonlinear systems with delay. One numerical example is provided to demonstrate the effectiveness of the results.

关键词： Stochastic Switching Delay System p-th Moment Stability Lyapunov-Razumikhin Approach

A Forecasting-based Distributed MPC Approach on Inventory Level Control of Supply Chain Network

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A Forecasting-based Distributed MPC Approach on Inventory Le...

Distributed PI Control for Synchronization in Directed Strongly Connected Complex Dynamical Networks

第43届中国控制会议

作者： Yu Sun Zhenqian Wang haibo gu Kexin Liu School of Automation Science and Electrical Engineering Beihang University

The development of economic globalization has led to an increasing complexity in supply chain networks(SCNs).However, the inventory control of SCNs has not been sufficiently investigated. In this paper, to maintain steady inventory levels for all entities in the SCN in the presence of demand fluctuations and uncertain lead times, we first propose a more realistic SCN model, within which each entity may have multiple providers and the in-transit stocks are excluded from the real ***, to mitigate the bullwhip effect, we employ a generic demand forecasting mechanism that only needs the historical information of consumers' demands. Finally, we introduce a forecasting-based distributed model predictive control(FDMPC)algorithm to keep the inventory levels of all entities steady and reduce the bullwhip effect. Numerical simulations confirm that the FDMPC approach effectively mitigates the bullwhip effect along the supply chain.

关键词： Supply Chain Network Inventory Control Model Predictive Control Forecasting

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Distributed PI Control for Synchronization in Directed Stron...