Bounded synchronization of complex dynamical networks with prescribed performance via event‐based transmission strategy

Abstract

This paper addresses a novel prescribed performance synchronization of complex dynamical networks by means of event-triggered communication protocols.With the designed controller and proposed even-triggered communication strategy, this paper have advantages of guaranteeing the transient and steady-state performance of complex dynamic networks and avoiding the continuous communication of networks for reducing the number of communications and saving the network resources. In addition, the Zeno behavior is avoided in the networks. At last, the effectiveness of the theoretic results obtained is verified via the application in the complex dynamical network with Chua's circuit.As we all know, in the past several years, with the rapid development of digital computers, the event-based communication schemes have received significant attention in signal processing. 24,25 Considering the event-based communication schemes, the information transmission from the sensors to the networks is permitted only when a particular condition of the event trigger function holds. Therefore, different from the common continuous transmission of information, the event-based communication mechanism can reduce the waste of network resources. To the present, the event-based communication synchronization problems of CNs have yielded considerable results. [26][27][28] Concretely, in the work of Li et al, 29 the authors studied the event-triggered intermittent communication synchronization problems for general directed CNs, which proposed a unified framework for synchronization and designed a newfangled distributed event-triggering sampling control method. For the Markovian jump CDNs with delayed, in the work of Zhou et al, 30 the researchers studied the exponential synchronization problems by proposing a novel randomly occurring event-based control method. The synchronization problems of CNs were investigated in the work of Dai et al 31 via distributed event-triggered communication method. Although the literary works mentioned earlier have contributed to the synchronization problem of event-driven communication in complex dynamic networks, the significance of the transient problem of synchronization course has not been considered.In fact, the transient performance of synchronization process is an important factor to consider. [32][33][34] In traditional synchronization course of CNs, the synchronization errors are testified to converge within a bounded set near zero, whose size decides by the designed parameters and some unknown bounded terms. Then, the prescribed performance control method 32 is raised to ensure that the tracking errors gather to a predefined bound accompanying with the convergence rate no less than a certain value. So far, the prescribed performance issues 32 have been expanded to the multiagent systems 35 and the complex dynamical (networks) systems. 36 However, the results proposed in related works 32-37 do not consider the event-triggered communication problem. As far as our knowledge is concerned, up to the present, no resul...

Saturated observer‐based adaptive neural network leader‐following control of N tractors with n‐trailers with a guaranteed performance

“…In order to guarantee prescribed transient and steady‐state performance characteristics, the prescribed performance control (PPC) methodology is presented in this section that was introduced in Reference 44 originally and its successful applications are found in the literature 45‐49,52 . The purpose of this technique is to force the tracking errors to evolve within predefined performance bounds gradually over the time.…”

“…According to a detailed literature review, 1‐41 main novelties and contributions of this article are clearly stated as follows:An observer‐based adaptive robust neural network leader‐following formation controller is proposed for N tractors each of which connected to n ‐trailers by taking both general forms of kinematic and dynamic models in the presence of model uncertainties which has not been addressed in the literature yet 1‐41 Compared with all previous works including References 18‐41, the proposed leader‐following formation controller ensures prescribed transient and steady‐state performance characteristics including convergence rate, undershoot/overshoot, and steady‐state error in order to provide a smooth transient response without unwanted large overshoots. The most of previous works that employ prescribed performance technique in the literature generally rely on the backstepping design procedure 1‐52 and, consequently, they suffer from an unwanted complexity and multiple control laws. However, the prescribe...…”

“…Meanwhile, the robot dynamics is not engaged in the design of the observer and unwanted peaking are also removed. Since system nonlinearities and prescribed performance nonlinear transformation impose a high degree of complexity and nonlinear terms in the open‐loop error dynamics, the traditional adaptive robust control methods could not simply compensate uncertain nonlinearities based on regression‐based adaptive update rules. Therefore, the employment of neural network and fuzzy approximation‐based control methods 43‐52 is strongly recommended to estimate and compensate unknown nonlinearities. In this article, an effective combination of a projection‐type radial basis function neural network (RBFNN) and an adaptive upper‐bounding saturation‐type robust controller is integrated into the controller design to compensate for unknown vehicle parameters, unmodeled dynamics, external disturbances, and NN approximation errors especially nonlinear‐in‐parameter ones.…”

Prescribed performance synchronization for time‐delayed complex dynamical networks under event‐triggered pinning control

“…Synchronization behavior, as the most significant topic among them, is extensively applied in secure communication, chemical and biological systems, and so forth 4‐6 . According to the requirement of practical problems, the synchronization patterns can be divided into the following categories: bounded synchronization, 7,8 cluster synchronization, 9 exponential synchronization, 10 and so forth 11 …”

“…Synchronization behavior, as the most significant topic among them, is extensively applied in secure communication, chemical and biological systems, and so forth. [4][5][6] According to the requirement of practical problems, the synchronization patterns can be divided into the following categories: bounded synchronization, 7,8 cluster synchronization, 9 exponential synchronization, 10 and so forth. 11 Meanwhile, a large of effective control schemes are proposed to synchronize the states of the nodes, including sliding mode control, 12 adaptive control, 13 activation feedback control, 14 intermittent control, 15 and so forth.…”