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This paper considers a class of distributed aggregative games for first-order and second-order integrator-type multi-cluster systems, respectively. Two Nash equilibrium seeking algorithms are designed based on a distributed aggregation observer which is used to estimate the aggregations of the clusters. The convergence is proved by the input-to-state stable method. Moreover, the algorithms are applied to a class of location control problems, that is, distributed nonlinear placement problems for multi-cluster systems. Finally, some simulations are presented to illustrate the effectiveness of the designed algorithms. [ABSTRACT FROM AUTHOR]

In this article, a class of distributed quadratic games is considered over an undirected graph. The issue on the communication topology restriction is introduced and the players’ dynamics are with nonlinear dynamics and unknown time-varying perturbation. A distributed Nash equilibrium seeking algorithm is proposed based on a high-gain observer method, and the convergence is analyzed by the Lyapunov stability theory. It is shown that each player estimates the rival players’ states, and the errors between the players’ states and the Nash equilibrium are ultimately bounded by a small bound. Moreover, the presented algorithm is free of chattering phenomena because it is designed using the hyperbolic tangent function instead of the signum function to dominant the perturbation. The effectiveness of the proposed algorithm is validated via a simulation of the oligopoly game in which five firms produce the same products in a duopoly market structure. [ABSTRACT FROM AUTHOR]

Distributed optimization for uncertain nonlinear interconnected multi-agent systems is considered in this paper. The objective is to design distributed algorithms by using local information such that all the agents' outputs converge to the global optimal output. The problem is challenging due to unknown modeling uncertainties and nonlinear interconnections. First, a distributed algorithm composed of a distributed state observer and a distributed optimal output observer is presented for heterogeneous outputs. Next, it is shown that the objective can be achieved by employing solely a distributed optimal output observer if the agents' outputs are homogeneous. Finally, the algorithms' effectiveness is validated by an electrical power system composed of four-machine subsystems. [ABSTRACT FROM AUTHOR]

This paper studies the Nash equilibrium seeking problem for non-cooperative games subject to set and nonlinear inequality constraints. The cost function for each player and the constrained function are determined by all the players' decision variables. Each player is assigned a constrained set while all the players are subject to a coupling nonlinear inequality constraint. A continuous-time distributed seeking algorithm using local information interaction is proposed, where the players deliver/receive information unidirectionally over a directed network. In particular, a distributed observer is first introduced for each player to estimate all the others' decision variables. Then, by using these estimates, a seeking algorithm is synthesized with a projection operator. Based on the time-scale separation approach, it is shown that the proposed continuous-time distributed seeking algorithm guarantees the convergence of the strategy profile to an arbitrarily small neighborhood of the generalized Nash equilibrium satisfying a KKT condition. An illustrative example is finally presented to validate the theoretical results. [ABSTRACT FROM AUTHOR]