Finite Time Consensus Control for Nonlinear Heterogeneous Multi-agent Systems With Disturbances

This paper discusses the finite time consensus (FTC) issue of nonlinear heterogeneous multi-agent systems (HMASs) by combining integral sliding-mode control (SMC), event-triggered control (ETC) and pinning control methods. The SMC is constructed separately for first-order and second-order agents to assure that the system is not interfered by the nonlinearities and disturbances when the state trajectory of the system moves on the sliding surface. To stimulate the FTC of system, a novel control protocols are designed and a fully distributed ETC with adjustable trigger frequency only rely on the local information is introduced. Moreover, the Zeno behavior is eliminated and the range of pinning gain of each agent under directed topology is determined. Meanwhile, we also give the conditional criteria for the system to achieve FTC. Eventually, the correctness of the obtained conclusion is illustrated by several simulation examples.

Learning Impulsive Pinning Control of Complex Networks

In this paper, we present an impulsive pinning control algorithm for discrete-time complex networks with different node dynamics, using a linear algebra approach and a neural network as an identifier, to synthesize a learning control law. The model of the complex network used in the analysis has unknown node self-dynamics, linear connections between nodes, where the impulsive dynamics add feedback control input only to the pinned nodes. The proposed controller consists of the linearization for the node dynamics and a reorder of the resulting quadratic Lyapunov function using the Rayleigh quotient. The learning part of the control is done with a discrete-time recurrent high order neural network used for identification of the pinned nodes, which is trained using an extended Kalman filter algorithm. A numerical simulation is included in order to illustrate the behavior of the system under the developed controller. For this simulation, a 20-node complex network with 5 different node dynamics is used. The node dynamics consists of discretized versions of well-known continuous chaotic attractors.

Pinning synchronization control for multi-layer complex networks via adaptive fuzzy logic system

In this paper, the pinning synchronization problem for the multi-layer networks with dynamic uncertainties is studied. The dynamical uncertainties can be approximated by a fuzzy logic system, based on which, the pinning synchronization scheme is proposed. By using Lyapunov stability theorem, the sufficient condition is given that can ensure that the multi-layer networks can synchronize to the reference trajectory with designed adaptive law. Finally, a numerical example is given to verify the effectiveness of the proposed pinning control scheme.

Outer Synchronization of Complex-Variable Networks with Complex Coupling via Impulsive Pinning Control

In this paper, outer synchronization of complex-variable networks with complex coupling is considered. Sufficient conditions for achieving outer synchronization using static impulsive pinning controllers are first derived according to the Lyapunov function method and stability theory of impulsive differential equations. From these conditions, the necessary impulsive gains and intervals for given networks can be easily calculated. Further, an adaptive strategy is introduced to design universal controllers and avoid repeated calculations for different networks. Notably, the estimation algorithms of the impulsive gains and intervals are provided. Finally, three numerical examples are performed to verify the effectiveness of the main results.