A Distributed Resource Allocation Algorithm for the General Linear Multiagent Systems

Abstract

We study the distributed resource allocation problem for heterogeneous multiagent systems over an undirected graph, an essential issue in multiagent system coordinated control and complex network system control. The decision variable is subject to global equality and local convex set constraints, and the objective is smooth and convex. It aims to minimize the global objective function by exchanging neighboring information between agents. An adaptive distributed algorithm is designed using the distance function-based exact penalty function method. A state- and time-based triggering condition is designed to avoid continuous communication and reduce the communication burden. From a random initial state, the proposed algorithm asymptotically converges to the optimal value by means of LaSalle’s invariance principle. Finally, examples are provided to demonstrate the effectiveness of our algorithm.

Heterogeneous Unknown Multiagent Systems of Different Relative Degrees: A Distributed Optimal Coordination Design

“…Several remarkable works investigating the DOC problem for heterogenous MASs can be found in the literature [17], [32]- [35]. Authors in [34] proposed a solution assuming the gradients of local cost functions follow a specific form.…”

“…Furthermore, their DOC algorithm ensures exponential convergence. In [35], the authors presumed the same condition on agents dynamics as [17]. They developed a distributed control protocol to address the resource allocation application under inequality constraints.…”

“…The main contribution of [33] is to remove the restricting conditions on the agents dynamics. To do so, the authors exploited the double-layer open-loop structure (first class) to develop their optimization algorithm in contrast with algorithms presented in [17], [32], [34], [35] utilizing the integrated closed-loop structure (second class). They derived conditions ensuring the reference trajectories generated by the top layer are tractable by the physical agents.…”

“…• Despite the results in [17], [32]- [35], which consider heterogenous MASs without uncertainties or unknown parameters, this paper takes into account the heterogeneous unknown agents case.…”