Semi‐global leader‐following output consensus of heterogeneous multi‐agent systems with input saturation

Shi, Lei; Li, Yuanlong; Lin, Zongli

doi:10.1002/rnc.4291

Cited by 42 publications

(43 citation statements)

References 18 publications

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“…In the practical applications of MASs, the system performance is affected by various constraints, such as input saturation, [28][29][30] output constraint, 31,32 maximum curvature constraint, 33 error constraints, 34 and state constraints. [35][36][37] Once these constraints are violated, it will lead to system instability, significant performance decline, and even cause serious safety accidents.…”

Section: Introductionmentioning

confidence: 99%

Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

Yang

Xiao

Yin

et al. 2020

Intl J Robust & Nonlinear

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This article investigates the leader-follower consensus problem of a class of non-strict-feedback nonlinear multiagent systems with asymmetric time-varying state constraints (ATVSC) and input saturation, and an adaptive neural control scheme is developed. By introducing the distributed sliding-mode estimator, each follower can obtain the estimation of leader's trajectory and track it directly. Then, with the help of time-varying asymmetric barrier Lyapunov function and radial basis function neural networks, the controller is designed based on backstepping technique. Furthermore, the mean-value theorem and Nussbaum function are utilized to address the problems of input saturation and unknown control direction. Moreover, the number of adaptive laws is equal to that of the followers, which reduces the computational complexity. It is proved that the leader-follower consensus tracking control is achieved without violating the ATVSC, and all closed-loop signals are semiglobally uniformly ultimately bounded. Finally, the simulation results are provided to verify the effectiveness of the control scheme.

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Section: Introductionmentioning

confidence: 99%

Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

Yang

Xiao

Yin

et al. 2020

Intl J Robust & Nonlinear

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“…The reference trajectories and disturbances are described by an external particular agent in MASs, and the agents in MASs interact with each other via the communication network. The COR has been widely investigated because it can be applied to many problems including mobile robots synchronization, power balancing (see References for example). In the early works about the COR, it is commonly assumed that communication is continuous.…”

Section: Introductionmentioning

confidence: 99%

Distributed adaptive integral‐type event‐triggered cooperative output regulation of switched multiagent systems by agent‐dependent switching with dwell time

Zhao

2020

Intl J Robust & Nonlinear

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Summary This article presents a distributed adaptive integral‐type event‐triggered scheme (ETS) and an agent‐dependent switching strategy with dwell time to solve the cooperative output regulation problem for switched multiagent systems. First, by constructing an adaptive law to dynamically update the time‐varying coupling weights for all the communication links, a fully distributed ETS is designed, where only the local information of the topology is adopted. Based on the integral‐type triggering condition, the interevent interval is substantially enlarged and Zeno behavior is explicitly ruled out. Second, each agent permits all the subsystems to be unstabilizable. The switching signal for each agent is different, and any adjacent switches of each agent satisfy the preset dwell time. Under the designed switching strategy, the solvability of the regulation problem is guaranteed. Finally, the effectiveness of the designed ETS and switching strategy is substantiated by an example.

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“…In fact, static gain control technique is also a very effective method . Moreover, based on this approach, many scholars have done a great number of works; see the works of Zhang et al, Shi et al and Zhang et al, for more discussions. Despite their efforts, as far as we know, the static gain technique has not been used to deal with the tracking control problem for strict‐feedback nonlinear time‐delay MASs with input saturation, which promotes this paper.…”

Section: Introductionmentioning

confidence: 99%

Tracking control for nonlinear time‐delay multiagent systems with input saturation

Duan

Zhang

Kong

et al. 2019

Adaptive Control & Signal

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Summary In this paper, the tracking control problem for a class of nonlinear time‐delay multiagent systems with input saturation is considered. The nonlinear dynamics are dominated by strict‐feedback form and satisfy Lipschitz conditions with constant gains. First, it indicated that the tracking control problem is equivalent to a general bound problem of high‐dimensional multivariable systems. Second, an ingenious state transformation is utilized to change the bound problem into the parameter design problem. Third, by the static gain control technique and the hyperbolic tangent function, both state feedback and output feedback controllers are built such that all signals of the closed‐loop systems are globally bounded, and the tracking errors between the followers and the leader can converge to a small neighborhood around the origin by appropriately selecting parameters. Finally, an example is shown to verify the feasibility of our results.

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Semi‐global leader‐following output consensus of heterogeneous multi‐agent systems with input saturation

Cited by 42 publications

References 18 publications

Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

Distributed adaptive integral‐type event‐triggered cooperative output regulation of switched multiagent systems by agent‐dependent switching with dwell time

Tracking control for nonlinear time‐delay multiagent systems with input saturation

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