Non-cooperative Game Model Based Bandwidth Scheduling and the Optimization of Quantum-Inspired Weight Adaptive PSO in a Networked Learning Control System

摘要

In this paper, under a framework of Networked twolayer Learning Control Systems (NLCSs), optimal network scheduling is studied. Multi networked feedback control loops called subsystems in a NLCS share common communication media and therefore there is a competition for available bandwidth and data rate. A non-cooperative game(NG) model is first formulated for the problem studied. The existence and uniqueness of Nash Equilibrium point is proved. Subsequently, the utility function of subsystems is designed, taking account of both transmission data rate and control sampling period according to the feature of scheduling pattern and network control. Following this, a quantum-inspired weight adaptive particle swarm optimization algorithm is developed to obtain an optimal solution. Simulation results presented in the paper have demonstrated the effectiveness of the proposed theoretical approach and the algorithm developed.