An RNN-Based Algorithm for Decentralized-Partial-Consensus Constrained Optimization
Zicong Xia, Yang Liu, Jianlong Qiu, Qihua Ruan, Jinde Cao · IEEE Transactions on Neural Networks and Learning Systems · 2021
This technical note proposes a decentralized-partial-consensus optimization (DPCO) problem with inequality constraints. The partial-consensus matrix originating from the Laplacian matrix is constructed to tackle the partial-consensus constraints. A continuous-time algorithm based on multiple interconnected recurrent neural networks (RNNs) is derived to solve the optimization problem. In addition, based on nonsmooth analysis and Lyapunov theory, the convergence of continuous-time algorithm is further proved. Finally, several examples demonstrate the effectiveness of main results.