Optimal resource allocation for high‐order nonlinear uncertain multi‐agent systems

Abstract

This article investigates the optimal resource allocation of nonlinear high-order multi-agent systems with coupling uncertainties. The objective is to design an output-feedback distributed algorithm for each agent to optimize the global cost function under network constraints. The global cost function is the sum of local cost functions. The available information to design the algorithm for each agent is only its own output and cost function, the outputs of its neighbors. To address the key technical challenge arising from the uncertainties and nonlinearities of network systems, a novel distributed resource allocation algorithm is proposed using active disturbance rejection strategy. The simulation results in the economic dispatch of a smart grid validate the effectiveness of the proposed method.

Distributed optimization of high‐order nonlinear multi‐agent systems with disturbance under switching topologies

“…Compared with the results 18‐20 for high‐order ideal MASs, in this article, the distributed optimization problems for high‐order nonlinear MASs with disturbance are addressed. Additionally, in the view of topology requirements, the new presented distributed algorithms can be deployed to high‐order MASs under switching digraphs, which is typically different from methods in literatures 18‐25 . In summary, the new proposed distributed algorithms overcome multiple practical constraints (e.g., high‐order MASs, nonlinearity, disturbance, switching digraphs) simultaneously, which have advantages over existing distributed optimization algorithms. The embedded technique 22 is not adopted in our algorithms design, that is, the extra optimal reference signal generator is not required.…”

“…Notice that the authors of literatures 9‐17 investigated distributed optimization problems based on first‐order MASs. However, the control objects are generally modeled as high‐order MASs 18‐25 in many real scenarios. Therefore, the distributed optimization of high‐order MASs was widely explored by many researchers.…”

“…As a further investigation of topology requirements in methods, 21‐23 the distributed optimization algorithms were extended to high‐order nonlinear MASs under fixed and weight balanced digraphs 24 . In addition, it is noticed that MASs may be disturbed in actual deployments, thus, the authors of literatures 17,23,25 took disturbance into considerations. Note that the existing distributed optimization methods 18‐25 for high‐order ideal/nonlinear/disturbed MASs require that the graphs are fixed.…”

“…In addition, it is noticed that MASs may be disturbed in actual deployments, thus, the authors of literatures 17,23,25 took disturbance into considerations. Note that the existing distributed optimization methods 18‐25 for high‐order ideal/nonlinear/disturbed MASs require that the graphs are fixed. Consequently, the distributed optimization of high‐order nonlinear MASs with disturbance under switching digraphs is still worth investigating.…”

Distributed finite‐time optimization algorithms for multi‐agent systems under directed graphs

“…In the past decades, distributed optimization problems in multi-agent systems (MASs) 1 have received increasing concerns due to widespread applications, such as mobile robots, 2,3 wireless sensor network, 4,5 and smart grid. 6,7 Distributed optimization in MASs is that states of all agents reach consensus at optimal point which refers to the unique minimizer of the sum of the local cost functions known by each agent.…”