Fixed-Time Distributed Optimization Without Matrix Inversion via Zeroing Neural Networks
A distributed optimization algorithm integrating distributed gradient estimation and the prediction-correction method is designed that can achieve fixed-time convergence, and the inverse of the Hessian matrix is approximated online using a zeroing neural network, which significantly improves computational efficiency.