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In this paper, we are concerned with the output tracking consensus matter for a class of pure-feedback nonlinear multi-agent systems (MASs) with actuator failures comprising loss of effectiveness and bias. Taking advantage of relative information from individual agents and their neighbors, a distributed adaptive fault-tolerant control strategy is proposed recursively by the approximation property of neural networks (NNs), backstepping methods, dynamic surface control (DSC) methodology and algebraic graph theory. The distinct features of this control approach are that it is not of requirement of prior information of individual agents with the help of approximation property, and the online update parameters are the norms of NNs weight vectors instead of weight vectors themselves. Also, it reduces the computational burden considerably by introducing the DSC approach. The stability of the resulting closed-loop system is rigorously investigated and it is proven that the consensus tracking errors of the MASs under directed communication topology converge to a small adjustable neighborhood around the origin in spite of actuator failures. Two simulation examples, both practical and numerical ones, are presented to verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The consensus tracking problem is discussed for a class of multi-agent systems (MASs) in non-affine pure-feedback form via output feedback approach under switching directed topologies. Observers are employed to reconstruct state information of the system, and then a consensus tracking control scheme is presented by the backstepping method combining with dynamic surface control (DSC) technique, neural networks (NNs), and graph theory. The main advantage of the proposed strategy is that it only relies on the output signals of individual agents in communication graph and it removes the requirement for exact priori knowledge about parameters of agents. Moreover, by introducing DSC technology, it avoids the well known problem of ‘explosion of complexity’ that conventional backstepping method suffers from along with the increasement of the degree of individual agents. It is proven that the designed output feedback control scheme guarantees consensus errors are cooperatively semiglobally uniformly ultimately bounded and converge to neighborhood of the origin by suitable choice of design parameters. Simulation results are presented to demonstrate the effectiveness of the proposed control approach. [ABSTRACT FROM AUTHOR]

This paper focuses on a class of nonlinear switching multi-agent systems about event-triggered adaptive tracking control. Compared with existing results, the event-triggered mechanism is first employed in nonlinear switched multi-agent systems with unknown parameters, and it can reduce the amount of computation and the frequency of the controller updates. By utilizing the backstepping technology, adaptive laws are designed to analyze the unknown parameters. In the sequel, all signals of multi-agent systems are bounded, the tracking errors converge to a small neighborhood of the origin. Finally, simulation results verify the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper is concerned with the privacy-preserving average consensus problem for discrete-time multi-agent systems. The main goal of this paper is to develop a privacy-preserving algorithm that ensures all agents in the network to reach exact average consensus while keeping the initial state of each agent private. To achieve this, a novel two-phase privacy-preserving algorithm is proposed. In the first phase, each agent generates a group of independent random signals and creates a mask signal via local data exchange. In the second phase, all agents execute a standard consensus algorithm. Rigorous analysis shows that each agent can converge to exact average consensus while protecting sensitive information of individuals against internal honest-but-curious nodes and external eavesdroppers. Moreover, the developed algorithm is applied to the distributed load sharing of microgrids. Finally, a simulation example is provided to verify the theoretical results. [ABSTRACT FROM AUTHOR]