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distributed adaptive control for synchronization of unknown nonlinear networked systems

AUTOMATICA 2010年第12期46卷 2014-2021页

作者： Das, Abhijit Lewis, Frank L. Univ Texas Arlington Automat & Robot Res Inst Ft Worth TX USA

This paper is concerned with synchronization of distributed node dynamics to a prescribed target or control node dynamics A design method is presented for adaptive synchronization controllers for distributed systems having non-identical unknown nonlinear dynamics and for a target dynamics to be tracked that is also nonlinear and unknown The development is for strongly connected digraph communication structures A Lyapunov technique is presented for designing a robust adaptive synchronization control protocol The proper selection of the Lyapunov function is the key to ensuring that the resulting control laws thus found are implementable in a distributed fashion Lyapunov functions are defined in terms of a local neighborhood tracking synchronization error and the Frobenius norm The resulting protocol consists of a linear protocol and a nonlinear control term with adaptive update law at each node Singular value analysis is used It is shown that the singular values of certain key matrices are intimately related to structural properties of the graph (C) 2010 Elsevier Ltd All rights reserved

关键词： Nonlinear multiagent systems distributed adaptive control Synchronization Consensus Networked systems

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distributed adaptive control FOR SYNCHRONIZATION IN DIRECTED COMPLEX NETWORKS

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SIAM JOURNAL ON control AND OPTIMIZATION 2015年第5期53卷 2980-3005页

作者： Yu, Wenwu Lu, Jinhu Yu, Xinghuo Chen, Guanrong Southeast Univ Dept Math Nanjing 210096 Jiangsu Peoples R China RMIT Univ Sch Elect & Comp Engn Melbourne Vic 3001 Australia Chinese Acad Sci Acad Math & Syst Sci Inst Syst Sci LSC Beijing 100190 Peoples R China City Univ Hong Kong Dept Elect Engn Hong Kong Hong Kong Peoples R China

The dynamics of a complex network is generally very complicated due to the self-dynamics of the node and their interactions. Many existing conditions for reaching certain desirable dynamics in a complex network require global information of the network, for example, the spectrum of its Laplacian matrix. A challenging problem is how the network structure affects the network dynamics in a distributed way especially for directed networks, which is still unclear today. This paper investigates the impact of the network structure on a general directed complex network and develops a scheme to change the weights in a local manner to achieve a desired behavior. In particular, network synchronization is investigated, for which some distributed adaptive laws are designed on the coupling weights for reaching synchronization in a directed complex network. It is found that the directed spanning tree structure is helpful while the aggregation and circular structures are harmful for achieving network synchronization. It is also found that the designed adaptive scheme on the weight of an edge in the network depends on the relative states between the terminal node and both of its inner and outer neighboring nodes, which reveals that the local information exchange in the terminal nodes is very important for reaching synchronization in directed complex networks.

关键词： synchronization complex network distributed adaptive control directed spanning path directed spanning tree

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distributed adaptive control for multiple under-actuated Lagrangian systems under fixed or switching topology

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NONLINEAR DYNAMICS 2018年第3期93卷 1705-1718页

作者： Chen, Ti Shan, Jinjun Ramkumar, Ganesh York Univ Dept Earth & Space Sci & Engn 4700 Keele St Toronto ON M3J 1P3 Canada

This paper presents distributed adaptive tracking control algorithms under fixed or switching communication graph for a team of agents, each of which is a special class of under-actuated Lagrangian system with uncertain parameters. The reference velocities of the unactuated and actuated variables are defined by an auxiliary system and the summation of the synchronization error and its integral, respectively. Based on such reference velocities and the linear-in-parameter property, distributed adaptive tracking controllers are designed for fixed graph with globally reachable leader, switching graph with globally reachable leader in each dwell time and switching graph with jointly globally reachable leader. Theoretical analyses are presented to demonstrate the convergence conditions of the proposed controllers. Finally, numerical simulations and experimental studies are performed to verify the effectiveness of the distributed adaptive tracking controllers.

关键词： distributed adaptive control Consensus Under-actuated Lagrangian systems Switching topology

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distributed adaptive control for Asymptotically Consensus Tracking of Uncertain Nonlinear Systems With Intermittent Actuator Faults and Directed Communication Topology

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IEEE TRANSACTIONS ON CYBERNETICS 2021年第8期51卷 4050-4061页

作者： Long, Jiang Wang, Wei Huang, Jiangshuai Zhou, Jing Liu, Kexin Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Beihang Univ Beijing Adv Innovat Ctr Big Data & Brain Comp Beijing 100191 Peoples R China Chongqing Univ Sch Automat Chongqing 400044 Peoples R China Univ Agder Dept Engn Sci N-4898 Grimstad Norway

In this article, we investigate the output consensus tracking problem for a class of high-order nonlinear systems with unknown parameters, uncertain external disturbances, and intermittent actuator faults. Under the directed topology conditions, a novel distributed adaptive controller is proposed. The common time-varying trajectory is allowed to be totally unknown by part of subsystems. Therefore, the assumption on the linearly parameterized trajectory signal in most literature is no longer needed. To achieve the relaxation, extra distributed parameter estimators are introduced in all subsystems. Besides, to handle the actuator faults occurring at possibly infinite times, a new adaptive compensation technique is adopted. It is shown that with the proposed scheme, all closed-loop signals are globally uniformly bounded and asymptotically output consensus tracking can be achieved.

关键词： Actuators Trajectory Topology Nonlinear systems Adaptation models Multi-agent systems adaptive control Asymptotically consensus tracking directed topology distributed adaptive control intermittent actuator faults multiagent systems (MASs)

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distributed adaptive control for a class of leader-following heterogeneous networks under intermittent communication environment

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IET control THEORY AND APPLICATIONS 2020年第15期14卷 2213-2222页

作者： Liu, Heng Wang, Xin Zhu, Jun-Wei Zhang, Xian Heilongjiang Univ Sch Math Sci Harbin 150080 Peoples R China Heilongjiang Univ Heilongjiang Prov Key Lab Theory & Computat Compl Harbin 150080 Peoples R China Zhejiang Univ Technol Dept Automat Hangzhou 310032 Peoples R China

This paper addresses the distributed adaptive tracking control problem for a class of multi-agent systems under intermittent communication constraints, where the dynamics of each follower subsystem contain heterogeneous mismatched affine uncertainties. Although some distributed adaptive consensus protocols were developed in previous work, several potential limitations of adaptive consensus controller design are difficult to overcome when the switching communication topology contains asymmetrical architecture and discontinuous failures. To overcome the main obstacles, the authors propose a novel adaptive coordination control algorithm such that the follower subsystems are enabled to track the states of a leader. By using the neighbourhood information, a distributed estimator like-protocol is constructed, under which, each subsystem can estimate the desire state information even under the intermittent connection constraint in directed switching topology. Then, in view of heterogeneous mismatched affine uncertainties, a decentralised adaptive controller with updating local parameters is presented to guarantee that each agent states track desire trajectories. Technically, by exploiting topology-dependent multiple Lyapunov functions approach, S-procedure technique and adaptive mechanism, the synchronisation conditions of the adaptive consensus algorithm are established to prove the synchronisation of heterogeneous agents even in the presence of intermittent communication failures. Finally, an example demonstrates the effectiveness for the proposed method.

关键词： multi-agent systems adaptive control Lyapunov methods synchronisation distributed control control system synthesis decentralised control uncertain systems intermittent connection constraint directed switching topology heterogeneous mismatched affine uncertainties decentralised adaptive controller adaptive consensus algorithm heterogeneous agents intermittent communication failures distributed adaptive control leader-following heterogeneous networks intermittent communication environment distributed adaptive tracking control problem multiagent systems intermittent communication constraints follower subsystem distributed adaptive consensus protocols adaptive consensus controller design switching communication topology adaptive coordination control neighbourhood information distributed estimator like-protocol topology-dependent multiple Lyapunov functions S-procedure technique

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distributed adaptive control for multiple nonholonomic systems with nonlinearly parameterized uncertainties

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INTERNATIONAL JOURNAL OF adaptive control AND SIGNAL PROCESSING 2019年第5期33卷 747-766页

作者： Gu, Jianzhong Li, Wuquan Yang, Hongyong Ludong Univ Sch Math & Stat Sci Yantai 264025 Peoples R China Ludong Univ Sch Informat & Elect Engn Yantai Peoples R China

This paper investigates the distributed adaptive control problem for multiple nonholonomic systems with nonlinearly parameterized uncertainties. Under the assumption that the graph topology is directed and the leader is globally reachable, distributed adaptive controllers are designed recursively by using backstepping technique and algebra graph theory. It is shown that all the followers' outputs will exponentially converge to the reference output signal while all the signals of the closed-loop system are bounded. Finally, two simulation examples are given to demonstrate the effectiveness of the control scheme.

关键词： directed network topology distributed adaptive control multiple nonholonomic systems

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distributed adaptive control: A theory of the Mind, Brain, Body Nexus

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BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES 2012年 1卷 55-72页

作者： Verschure, Paul F. M. J. Catalan Inst Res & Adv Studies ICREA Ctr Autonomous Syst & Neurorobot Lab Synthet Percept Emot & Cognit Syst SPECS Barcelona Spain Univ Pompeu Fabra Barcelona Spain

distributed adaptive control (DAC) is a theory of the design principles underlying the Mind, Brain, Body Nexus (MBBN) that has been developed over the last 20 years. DAC assumes that the brain maintains stability between an embodied agent and its environment through action. It postulates that in order to act, or know how, the brain has to answer four fundamental questions: why, what, where, when. Thus the function of the brain is to continuously solve the, so called, H4W problem. The DAC theory is expressed as a robot based neural architecture organized in two complementary structures: layers and columns. The organizational layers are called: reactive, adaptive and contextual and its columnar organization defines the processing of states of the world, the self and the generation of action. Each layer is described with respect to its key hypotheses, implementation and specific benchmarks. After this overview of the key elements of DAC, the mapping of its key assumptions towards the invertebrate and mammalian brain is described. In particular, this review will focus on the systems involved in realizing the core principles underlying the reactive layer: the allostatic control of fundamental behavior systems in the vertebrate brain and the emergent non-linearity through neuronal mass action in the locust brain. The adaptive layer will be analyzed in terms of the classical conditioning paradigm and its neuronal substrate the amygdala-cerebellum-neocortex complex together with episodic memory and the formation of sense-act couplets in the hippocampus. For the contextual layer the ability of circuits in the prefrontal cortex to acquire and express contextual plans for action is described. The general overview of DAC's explanation of MBBN is combined by examples of application scenarios in which DAC has been validated including mobile and humanoid robots, neurorehabilitation and the large-scale interactive space Ada. After 20 years of research DAC can be considered a mature

关键词： Architecture Body Brain distributed adaptive control Mind Robot

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distributed adaptive control and stability verification for linear multiagent systems with heterogeneous actuator dynamics and system uncertainties

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INTERNATIONAL JOURNAL OF control 2019年第11期92卷 2620-2638页

作者： Dogan, K. Merve Gruenwald, Benjamin C. Yucelen, Tansel Muse, Jonathan A. Butcher, Eric A. Univ S Florida Dept Mech Engn Tampa FL 33620 USA Air Force Res Lab Wright Patterson AFB OH USA Univ Arizona Dept Aerosp & Mech Engn Tucson AZ 85721 USA

The contribution of this paper is a control synthesis and stability verification framework for linear time-invariant multiagent systems with heterogeneous actuator dynamics and system uncertainties. In particular, we first propose a distributed adaptive control architecture in a leader-follower setting for this class of high-order multiagent systems. The proposed architecture uses a hedging method, which alters the ideal reference model dynamics of each agent in order to ensure correct adaptation in the presence of heterogeneous actuator dynamics of these agents. We then use Lyapunov stability theory and linear matrix inequalities to analyse the proposed architecture. This analysis reveals a stability condition, where evaluation of this condition with respect to a given graph topology allows stability verification of the controlled multiagent system. From a practical point of view, this condition also shows a fundamental tradeoff between heterogeneous agent actuation capabilities and unknown parameters in agent dynamics. Several illustrative numerical examples are also provided to demonstrate the efficacy of the proposed architecture.

关键词： Multiagent systems actuator dynamics system uncertainty distributed adaptive control linear matrix inequalities stability verification

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A bottom up approach towards the acquisition and expression of sequential representations applied to a behaving real-world device: distributed adaptive control III

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NEURAL NETWORKS 1998年第7-8期11卷 1531-1549页

作者： Verschure, PFMJ Voegtlin, T Univ Zurich ETH Inst Neuroinformat CH-8006 Zurich Switzerland Ecole Normale Super Lyon France

Biological systems display a high degree of flexibility in problem solving. In this paper a model is presented, distributed adaptive control III (DACIII), which is aimed at understanding these forms of behavior. DACIII is part of a larger modeling series directed at understanding how biological systems acquire, retain, and express knowledge of the world. This modeling series has its roots, on one hand, in the methodological consideration that brain and behavior need to be modeled from a multi-level perspective. On the other, the importance of the acquisition of representations of events in the world, as opposed to an a priori specification, is emphasized. DACIII is presented against the background of the paradigms of classical and operant conditioning. On the basis of an analysis of these experimental approaches towards the study of animal behavior a theoretical framework is defined aimed at identifying the minimal requirements of a control structure which could display these behaviors. The proposed model is evaluated in different configurations using both simulated and real robots. It is demonstrated that DACIII is able to fully bootstrap itself from a mode of control which solely relies on proximal sensors and predefined reflexes, to a level of control which is dominated by acquired representations of events transduced by distal sensors. This transition is reflected in the performance of the behaving device, from strongly variable trajectories to highly structured behavioral sequences. The results are compared with alternative models of classical and operant conditioning and models which attempt to capture the properties of its underlying neural substrate. (C) 1998 Elsevier Science Ltd. All rights reserved.

关键词： conditioning learning robot model brain sequential representations problem solving goal directed behavior distributed adaptive control foraging

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Attack reconstruction-based resilient consensus tracking for multi-agent systems with distributed adaptive control protocol

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR control 2024年第9期34卷 6165-6179页

作者： Li, Zifei Wang, Wei Huang, Jiangshuai Beihang Univ Sch Automat Sci & Elect Engn Beijing Peoples R China Zhongguancun Lab Beijing Peoples R China Chongqing Univ Sch Automat Chongqing Peoples R China

This article considers the distributed secure consensus tracking control problem for multi-agent systems (MASs) with relative output information. To tackle the potential false-data-injection (FDI) attacks on both the communication between physical components and the control center at the agent level, as well as the message transmission between connected agents, local sliding mode observers (SMO) and distributed observers are proposed for each agent. By introducing reconstructed signals for attacks and smooth terms to compensate the unknown input in the leader agent's dynamics, a distributed adaptive consensus protocol with relative output information is proposed. The closed-loop stability is analyzed by introducing a novel Lyapunov function. It is shown that all closed-loop signals are globally uniformly bounded and asymptotically consensus tracking can be achieved. Simulation results are provided to validate the theoretical findings.

关键词： distributed adaptive control false data injection attacks multi-agent systems

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