Abstract
This paper focuses on the problem of the event-triggered adaptive containment control for a class of nonlinear multiagent systems (MASs) with prescribed performance and immeasurable states. First, the radial basis function neural networks (RBFNNs) are adopted to approximate the uncertain smooth nonlinear function, and the neural network-based state observer is designed to estimate the unmeasurable state. Besides, to reduce the control resource consumption and get a better balance between the system performance and network constraints, the switching threshold-based event-triggered control strategy is introduced. Based on this, the novel distributed containment controller is designed by utilizing the adaptive backstepping technique and the dynamic surface control (DSC) technique to guarantee that the output of each follower converges to the convex hull formed by multileader. Moreover, the containment errors can be converged to the prescribed boundary and all signals in closed-loop system are semi-global uniformly ultimately bounded (SGUUB) as well. Finally, the simulation examples are carried out to illustrate the efficiency of the proposed controller.
Highlights
Over the past decades, cooperative control of multiagent systems (MASs) has gained growing popularity on account of its extensive applications in various fields, such as sensor networks [1] [2] and marine vessels [3] [4] as well as spacecraft formation flying [5], to name just a few
An adaptive fuzzy backstepping dynamic surface control (DSC) method was introduced for multiple-input and multiple-output (MIMO) nonlinear systems in [16]
The adaptive event-triggered containment control scheme has been investigated for a class of strict-feedback nonlinear MASs with prescribed performance and unmeasured states which can be estimated by NN-based observers
Summary
Cooperative control of multiagent systems (MASs) has gained growing popularity on account of its extensive applications in various fields, such as sensor networks [1] [2] and marine vessels [3] [4] as well as spacecraft formation flying [5], to name just a few. Networks (RBFNNs) to tackle the obstacle of uncertain nonlinearities and proposed the NN-based distributed adaptive containment control scheme for second-order MASs with unknown nonlinear dynamics. It is worth noting that the problems of event-triggered adaptive containment control for nonlinear MASs with immeasurable states and predefined performance are still to be studied. Motivated by the analysis mentioned above, this paper is concerned with the observer-based eventtriggered adaptive containment control problem for a class of high-order uncertain nonlinear multiagent systems in strict-feedback form with prescribed performance. The major contributions of this paper can be stated as follows: 1) By means of extending the switching threshold event-triggered strategy to the containment control of MASs, the communication burden has been alleviated and the system performance can be ensured.
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