Output Feedback Distributed Containment Control for High-Order Nonlinear Multiagent Systems

Li, Yafeng; Chen, Hua; Wu, Shuangshuang; Guan, Xinping

doi:10.1109/tcyb.2017.2655054

Cited by 63 publications

(18 citation statements)

References 28 publications

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“…, N + M. Remark 1. In the literature [7,24], it is assumed that the MASs will not show actuator faults at any time. However, due to machine aging or working environment, actuator faults are inevitable in actual industrial production.…”

Section: Problem Description and Preliminariesmentioning

confidence: 99%

“…In fact, nonlinear systems can better describe a practical engineering problem than linear systems, such as manipulator systems [19], inverted pendulum systems [20], and rigid robotic systems [21]. All systems models in [16][17][18] and practical application systems models in [19][20][21][22][23][24][25][26] are first-or second-order systems. For example, under the common assumption that each agent can only obtain the relative information of its neighbours intermittently, the containment control method was proposed for a class of second-order MASs with inherent nonlinear dynamics in [17].…”

Section: Introductionmentioning

confidence: 99%

“…So, it is of theoretical and practical value to study the containment control of high-order systems. Some containment control approaches were studied for high-order nonlinear MASs in [24][25][26]. Compared with loworder MASs, the containment control method for highorder nonlinear MASs is more difficult due to the complexity of high-order systems.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Fuzzy Cooperative Control for Nonlinear Multiagent Systems with Unknown Control Coefficient and Actuator Fault

et al. 2021

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In this paper, an adaptive fuzzy containment condtrol is considered for nonlinear multiagent systems, in which it contains the unknown control coefficient and actuator fault. The uncertain nonlinear function has been approximated by fuzzy logic system (FLS). The unknown control coefficient and the remaining control rate of actuator fault can be solved by introducing a Nussbaum function. In order to avoid the repeated differentiations of the virtual controllers, first-order filters are added to the traditional backstepping control method. By designing the maximum norm of ideal adaptive parameters, only one adaptive parameter needs to be adjusted online for each agent itself. An adaptive fuzzy containment controller is constructed through the backstepping control technique and compensating signals. It is demonstrated that all the signals in nonlinear multiagent systems are bounded by designing adaptive fuzzy containment controller, and all followers can converge to the convex hull built by the leaders. The simulation studies can further confirm the effectiveness of the proposed control method in this paper.

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Section: Problem Description and Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive Fuzzy Cooperative Control for Nonlinear Multiagent Systems with Unknown Control Coefficient and Actuator Fault

et al. 2021

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“…Further study of the cooperative control problem of multiagent systems, extending the consensus control of a single leader, considers multiagent cooperative control in the case of multiple leaders, and designs a controller to make the followers converge to a convex hull composed of multiple leaders, which is called containment control. As a special case of cooperative control, many research results of MASs containment control have been reported in the field of integer order control, such as adaptive control [12,13], feedback control [14,15], linear matrix inequalities (LMIs) [16,17], sliding mode control [18], and so on.…”

Section: Introductionmentioning

confidence: 99%

Switched Fractional Order Multiagent Systems Containment Control with Event-Triggered Mechanism and Input Quantization

Yuan

Chen

2022

Fractal Fract

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This paper studies the containment control problem for a class of fractional order nonlinear multiagent systems in the presence of arbitrary switchings, unmeasured states, and quantized input signals by a hysteresis quantizer. Under the framework of the Lyapunov function theory, this paper proposes an event-triggered adaptive neural network dynamic surface quantized controller, in which dynamic surface control technology can avoid “explosion of complexity” and obtain fractional derivatives for virtual control functions continuously. Radial basis function neural networks (RBFNNs) are used to approximate the unknown nonlinear functions, and an observer is designed to obtain the unmeasured states. The proposed distributed protocol can ensure all the signals remain semi-global uniformly ultimately bounded in the closed-loop system, and all followers can converge to the convex hull spanned by the leaders’ trajectory. Utilizing the combination of an event-triggered scheme and quantized control technology, the controller is updated aperiodically only at the event-sampled instants such that transmitting and computational costs are greatly reduced. Simulations compare the event-triggered scheme without quantization control technology with the control method proposed in this paper, and the results show that the event-triggered scheme combined with the quantization mechanism reduces the number of control inputs by 7% to 20%.

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“…Therefore, high-order nonlinear systems have been universally studied. For example, [32,33] investigated containment problems and consensus problems of high-order nonlinear systems, respectively. However, to the best of our knowledge, there are no results about noncooperative games of high-order nonlinear multi-agent systems over weight-unbalanced digraphs.…”

Section: Introductionmentioning

confidence: 99%

Distributed Nash Equilibrium Seeking for Noncooperative Games of High-Order Nonlinear Multi-Agent Systems Over Weight-Unbalanced Digraphs

Deng¹,

Luo²

2021

Preprint

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In this paper, we investigate the noncooperative games of multi-agent systems. Different from existing noncooperative games, our formulation involves the high-order nonlinear dynamics of players, and the communication topologies among players are weight-unbalanced digraphs. Due to the high-order nonlinear dynamics and the weight-unbalanced digraphs, existing Nash equilibrium seeking algorithms cannot solve our problem. In order to seek the Nash equilibrium of the noncooperative games, we propose two distributed algorithms based on state feedback and output feedback, respectively. Moreover, we analyze the convergence of the two algorithms with the help of variational analysis and Lyapunov stability theory. By the two algorithms, the high-order nonlinear players exponentially converge to the Nash equilibrium. Finally, two simulation examples illustrate the effectiveness of the algorithms.

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Output Feedback Distributed Containment Control for High-Order Nonlinear Multiagent Systems

Cited by 63 publications

References 28 publications

Adaptive Fuzzy Cooperative Control for Nonlinear Multiagent Systems with Unknown Control Coefficient and Actuator Fault

Adaptive Fuzzy Cooperative Control for Nonlinear Multiagent Systems with Unknown Control Coefficient and Actuator Fault

Switched Fractional Order Multiagent Systems Containment Control with Event-Triggered Mechanism and Input Quantization

Distributed Nash Equilibrium Seeking for Noncooperative Games of High-Order Nonlinear Multi-Agent Systems Over Weight-Unbalanced Digraphs

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