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distributed adaptive consensus tracking for uncertain high-order nonlinear multiagent systems with event-triggered communication

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OPTIMAL control APPLICATIONS & METHODS 2020年第6期41卷 2077-2093页

作者： Long, Jiang Wang, Wei Huang, Jiangshuai Fan, Huijin Beihang Univ Sch Automat Sci & Elect Engn Beijing Peoples R China Beihang Univ Beijing Adv Innovat Ctr Big Data & Brain Comp Beijing Peoples R China Chongqing Univ Sch Automat Chongqing Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Natl Key Lab Sci & Technol Multispectral Informat Wuhan 430074 Peoples R China

This article investigates the distributed adaptive consensus tracking control problem for a class of high-order nonlinear multiagent systems with unmodeled system dynamics, uncertain external disturbances, and event-triggered communication. Under an undirected graph condition, a robust distributed adaptive consensus control scheme is proposed. To deal with the lumped system uncertainties involved in each agent, adaptive compensation techniques are adopted. Moreover, by designing a triggering condition for each agent, which only relies on individual states' changing rates, continuous monitoring of neighboring states can be avoided. It is shown that with the proposed control scheme, all the closed-loop signals are globally uniformly bounded and all the agents' outputs can track the desired trajectory with adjustable tracking errors. Meanwhile, Zeno behavior is excluded in each agent.

关键词： distributed adaptive control event-triggered communication output consensus tracking uncertain nonlinear systems

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An embodied biologically constrained model of foraging: from classical and operant conditioning to adaptive real-world behavior in DAC-X

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NEURAL NETWORKS 2015年 72卷 88-108页

作者： Maffei, Giovanni Santos-Pata, Diogo Marcos, Encarni Sanchez-Fibla, Marti Verschure, Paul F. M. J. UPF Ctr Autonomous Syst & Neurorobot Lab Synthet Percept Emot & Cognit Syst SPECS Barcelona Spain ICREA Barcelona Spain

Animals successfully forage within new environments by learning, simulating and adapting to their surroundings. The functions behind such goal-oriented behavior can be decomposed into 5 top-level objectives: 'how', 'why', 'what', 'where', 'when' (H4W). The paradigms of classical and operant conditioning describe some of the behavioral aspects found in foraging. However, it remains unclear how the organization of their underlying neural principles account for these complex behaviors. We address this problem from the perspective of the distributed adaptive control theory of mind and brain (DAC) that interprets these two paradigms as expressing properties of core functional subsystems of a layered architecture. In particular, we propose DAC-X, a novel cognitive architecture that unifies the theoretical principles of DAC with biologically constrained computational models of several areas of the mammalian brain. DAC-X supports complex foraging strategies through the progressive acquisition, retention and expression of task-dependent information and associated shaping of action, from exploration to goal-oriented deliberation. We benchmark DAC-X using a robot-based hoarding task including the main perceptual and cognitive aspects of animal foraging. We show that efficient goal-oriented behavior results from the interaction of parallel learning mechanisms accounting for motor adaptation, spatial encoding and decision-making. Together, our results suggest that the H4W problem can be solved by DAC-X building on the insights from the study of classical and operant conditioning. Finally, we discuss the advantages and limitations of the proposed biologically constrained and embodied approach towards the study of cognition and the relation of DAC-X to other cognitive architectures. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Goal-oriented behavior Cognitive architecture Robot Foraging distributed adaptive control

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Event-Triggered distributed adaptive Leaderless Consensus of Uncertain Heterogenous Nonlinear Multi-Agent Systems

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2024年第5期71卷 2694-2698页

作者： Liu, Yuxiao Wu, Xiangkai Long, Jiang Wang, Wei Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Northwestern Polytech Univ Sch Comp Sci Xian 710072 Shaanxi Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Zhongguancun Lab Beijing 100191 Peoples R China

This brief investigates the leaderless consensus control problem for a class of heterogenous uncertain nonlinear multi-agent systems with event-triggered communication. Different from most of currently available results, the system orders of all the agents are allowed to be nonidentical. To address this issue, a novel distributed reference system is first proposed for each agent, by using the discrete outputs of its own and its neighbors. To alleviate the communication burden among the connected agents, a triggering condition without continuous monitoring of neighboring states is designed for each agent to decide when to transmit its output to its neighbors. Then, a fully distributed adaptive backstepping based leaderless consensus control scheme is presented. It is proved that all the closed-loop signals are globally uniformly bounded and the outputs of all the agents can achieve asymptotical average consensus. Besides, Zeno behavior is excluded for each agent. Finally, the effectiveness of the proposed control scheme is verified in simulation.

关键词： distributed adaptive control nonlinear multi-agent systems leaderless consensus event-triggered communication

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adaptive synchronisation of unknown nonlinear networked systems with prescribed performance

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2017年第4期48卷 885-898页

作者： Hashim, Hashim. A. El-Ferik, Sami Lewis, Frank L. King Fahd Univ Petr & Minerals Syst Engn Dhahran Saudi Arabia Univ Texas Arlington Dept Elect Engn Ft Worth TX USA

This paper proposes an adaptive tracking control with prescribed performance function for distributive cooperative control of highly nonlinear multi-agent systems. The use of such approach confines the tracking error within a large predefined set to a predefined smaller set. The key idea is to transform the constrained system into unconstrained one through the transformation of the output error. Agents' dynamics are assumed unknown, and the controller is developed for a strongly connected structured network. The proposed controller allows all agents to follow the trajectory of the leader node, while satisfying the necessary dynamic requirements. The proposed approach guarantees uniform ultimate boundedness for the transformed error as well as a bounded adaptive estimate of the unknown parameters and dynamics. Simulations include two examples to validate the robustness and smoothness of the proposed controller against highly nonlinear heterogeneous multi-agent system with uncertain time-variant parameters and external disturbances.

关键词： Prescribed performance transformed error multi-agents networked systems distributed adaptive control

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distributed adaptive coordinated tracking for coupled non-holonomic mobile robots

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IET control THEORY AND APPLICATIONS 2014年第18期8卷 2336-2345页

作者： Qiu, Yilong Xiang, Linying Xiamen Univ Dept Automat Xiamen 361005 Fujian Peoples R China

In this study, a coordinated tracking control problem is studied for coupled non-holonomic mobile robots with limited information of a reference trajectory. A distributed control law with adaptive time-varying gains is proposed to guarantee that the robots can form a prespecified geometric pattern while the centroid of the geometric pattern can track the reference signal. By designing the adaptive control gains, the control algorithm of this paper does not require the global knowledge of the upper bound of the leader's control input. Both continuous and discontinuous adaptive protocols are proposed in this study. Finally, simulation examples are presented to verify the theoretical results.

关键词： mobile robots adaptive control distributed control time-varying systems control system synthesis trajectory control coordinated tracking control distributed adaptive control coupled nonholonomic mobile robot distributed control law adaptive time-varying gains geometric pattern adaptive control gains discontinuous adaptive protocol

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Neuro-adaptive cooperative tracking control with prescribed performance of unknown higher-order nonlinear multi-agent systems

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INTERNATIONAL JOURNAL OF control 2019年第2期92卷 445-460页

作者： Hashim, Hashim A. El-Ferik, Sami Lewis, Frank L. Univ Western Ontario Dept Elect & Comp Engn London ON Canada King Fahd Univ Petr & Minerals Dept Syst Engn Dhahran Saudi Arabia Univ Texas Arlington Dept Elect Engn UTA Res Inst Ft Worth TX USA

This paper is concerned with the design of a distributed cooperative synchronisation controller for a class of higher-order nonlinear multi-agent systems. The objective is to achieve synchronisation and satisfy a predefined time-based performance. Dynamics of the agents (also called the nodes) are assumed to be unknown to the controller and are estimated using neural networks. The proposed robust neuro-adaptive controller drives different states of nodes systematically to synchronise with the state of the leader node within the constraints of the prescribed performance. The nodes are connected through a weighted directed graph with a time-invariant topology. Only few nodes have access to the leader. Lyapunov-based stability proofs demonstrate that the multi-agent system is uniformly ultimately bounded stable. Highly nonlinear heterogeneous networked systems with uncertain parameters and external disturbances were used to validate the robustness and performance of the new novel approach. Simulation results considered two different examples: single-input single-output and multi-input multi-output, which demonstrate the effectiveness of the proposed controller.

关键词： Prescribed performance transformed error multi-agents neuro-adaptive distributed adaptive control consensus transient steady-state error

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Cooperative Output Regulation of Heterogeneous Unknown Systems via Passification-Based Adaptation

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IEEE control SYSTEMS LETTERS 2018年第1期2卷 151-156页

作者： Baldi, Simone Delft Univ Technol Delft Ctr Syst & Control NL-2628 Delft Netherlands

While several robust cooperative output regulation approaches for heterogeneous systems have been proposed (with fixed-gain distributed controllers), the design of adaptive-gain distributed controllers becomes relevant in dealing with larger uncertainty than robust approaches. This letter addresses the adaptive cooperative output regulation problem for heterogeneous systems with unknown linear dynamics, where possibly large system uncertainty would make fixed-gain robust approaches not applicable. A passification method is adopted to design adaptive-gain distributed controllers solving the problem. The proposed method includes two steps: in the first step, a distributed observer of the exogenous signal is designed for those systems that cannot access the exosystem, and a reference model is designed whose output can converge to the exogenous signal;in the second step, command generator tracking is achieved via adaptive laws that make the output of each system converge to the output of the reference model, and thus to the exogenous signal. Stability analysis is provided via a Lyapunov approach, and a numerical example illustrates the effectiveness of the approach.

关键词： Cooperative output regulation distributed adaptive control passification method

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Fully distributed adaptive Consensus Tracking of Uncertain Nonlinear Multi-Agent Systems: An Augmented System Approach

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2023年第6期70卷 2151-2155页

作者： Long, Jiang Guo, Yangming Liu, Zun Wang, Wei Zhou, Siwen Northwestern Polytech Univ Sch Comp Sci Xian 710072 Shaanxi Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China

In this brief, we investigate the consensus tracking control problem for first-order nonlinear multi-agent systems with unknown system parameters, external disturbances and directed communication graph. The system dynamics of each agent is not required to satisfy Lipschitz condition. Besides, the desired trajectory is not of linearly parameterized form with basis functions known by all the agents. In this setting, how to design a fully distributed adaptive control scheme to guarantee consensus tracking is a difficult issue since non-symmetric Laplacian matrix brings difficulties of designing fully distributed parameter update laws. To solve this issue, the design idea of transforming the original first-order multi-agent systems into augmented second-order multi-agent systems is firstly presented. Based on adaptive backstepping technique, a novel fully distributed consensus tracking control scheme is then proposed. Finally, the effectiveness of the proposed control scheme is verified in simulation.

关键词： distributed adaptive control nonlinear multi-agent systems consensus directed topology

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Decentralized Learning for Multi-player Multi-armed Bandits

Decentralized Learning for Multi-player Multi-armed Bandits

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51st IEEE Annual Conference on Decision and control (CDC)

作者： Kalathil, Dileep Nayyar, Naumaan Jain, Rahul Univ So Calif Dept Elect Engn Los Angeles CA 90089 USA

ISBN: (纸本)9781467320665

We consider the problem of distributed online learning with multiple players in multi-armed bandit models. Each player can pick among multiple arms. As a player picks an arm, it gets a reward from an unknown distribution with an unknown mean. The arms give different rewards to different players. If two players pick the same arm, there is a "collision", and neither of them get any reward. There is no dedicated control channel for coordination or communication among the players. Any other communication between the users is costly and will add to the regret. We propose an online index-based learning policy called dUCB4 algorithm that trades off exploration v. exploitation in the right way, and achieves expected regret that grows at most near-O(log(2)T). The motivation comes from opportunistic spectrum access by multiple secondary users in cognitive radio networks wherein they must pick among various wireless channels that look different to different users.

关键词： distributed adaptive control multi-armed bandits online learning multi-agent systems

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distributed adaptive Output Feedback Consensus Tracking of Uncertain Multi -Agent Systems with Communication Delays and Switching Typologies 17

Distributed Adaptive Output Feedback Consensus Tracking of U...

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17th Conference on Industrial Electronics and Applications (ICIEA)

作者： Zhang, Yaozhong Long, Jiang Wang, Wei Beihang Univ Sch Automat Sci & Elect Engn Beijing Peoples R China Northwestern Polytech Univ Sch Comp Sci Xian Peoples R China

ISBN: (纸本)9781665409841

This paper investigates the adaptive consensus tracking control problem for a class of high-order multi-agent systems in a strict feedback form under a directed topology condition. In contrast to the existing consensus tracking results, in this paper, unknown system parameters, immeasurable states, comnnmication delays and switching topologies of the multiagent systems are considered simultaneously. Given the fact that only the system output is available in the controller design, a group of state estimation filters is designed for each agent to observe its own and its neighbors' unmeasurable states. By incorporating adaptive backstepping technique with a novel Lyapunov-Krasovskii function, a distributed consensus tracking control scheme is then proposed under switching topology condition. It is shown that with the proposed control scheme, the boundedness of all the closed-loop signals can be guaranteed and the output of each agent can track the desired trajectory. Moreover, the tracking errors can be decreased by suitably adjusting design parameters. Finally, a numerical example is considered to validate the proposed control scheme.

关键词： distributed adaptive control output feedback consensus tracking communication delays switching topologies

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