Abstract-This paper addresses the fixed-time leader-follower consensus problem for high-order integrator multi-agent systems subject to matched external disturbances. A new cascade control structure, based on a fixedtime distributed observer, is developed to achieve the fixed-time consensus tracking control. A simulation example is included to show the efficacy and the performance of the proposed control structure with respect to different initial conditions.

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This paper deals with consensus disturbance rejection of network-connected dynamic systems using disturbance observers. The control objective of consensus disturbance rejection is to achieve a common state trajectory for the networkconnected subsystems that are under deterministic disturbances. The difference from the existing disturbance rejection methods is that only the relative state information is used for disturbance rejection, and as a consequence of using the relative state information, only the part of the disturbances that affect the common trajectories will be rejected. The conditions for designing disturbance observers for consensus control are identified for networked-connect multi-agent systems. Certain features of the individual subsystems are analysed for possible implementation of disturbance-observer based rejection, and the disturbance observers are designed based on the relative state information obtained from the neighbouring subsystems under different network connections. When the network connectivity is available for the disturbance observer design, consensus disturbance rejection is achieved for a directed network with a spanning tree. A fully distributed consensus disturbance rejection design is presented for an undirected network with the use of adaptive parameters for the estimation of the unknown network connectivity. Disturbance observers are also proposed for disturbance rejection in the leader-follower consensus control.

This paper deals with consensus output regulation of a class of nonlinear systems which consist of network-connected subsystems with unknown parameters. The subsystems may have different dynamics with uncertainties, and be subject to the disturbances generated from an exosystem. Only some subsystems have access to the desired output, which is also formulated as an output of the exosystem, following the standard formulation of output regulation of nonlinear systems. The proposed design makes use of some latest results on Laplacian matrices, and a new design of the internal model, which is based on known functions of with unknown constant parameters. Adaptive backstepping design techniques are integrated with the consensus control design to tackle the nonlinearity and unknown constant parameters in the system, and unknown functions relating to the state of the exosystem. The proposed control inputs and adaptive laws are fully decentralized, and ensure the asymptotic convergence to zero of the regulation errors.

This paper deals with adaptive consensus output regulation of a class of network-connected nonlinear systems with completely unknown parameters, including the high frequency gains of the subsystems. The subsystems may have different dynamics, as long as the relative degrees are the same. A new type of Nussbaum gain is proposed to deal with adaptive consensus control of network-connected systems without any knowledge of the high frequency gains. Adaptive laws and internal models are designed for the subsystems to deal with unknown parameters for tracking trajectories and unknown system parameters. In the control design, only the relative information of subsystem outputs are used, provided that regulation error of one of the subsystems is available. The proposed control inputs and the adaptive laws are decentralized. If the relative degree is one, only the relative subsystem outputs are exchanged. For the case of higher relative degrees, the nonlinear model structure of the subsystems is exploited for backstepping control design, and some variables generated by the subsystem controllers are exchanged among the subsystems in the neighbourhood defined by the connection graph.