A neurodynamic approach for nonsmooth optimal power consumption of intelligent and connected vehicles

Abstract

This paper investigates a class of power consumption minimization and equalization for intelligent and connected vehicles cooperative system. Accordingly, a distributed optimization problem model related to power consumption and data rate of intelligent and connected vehicles is presented, where the power consumption cost function of each intelligent and connected vehicle may be nonsmooth, and the corresponding control variable is subject to the constraints generated by data acquisition, compression coding, transmission and reception. We propose a distributed subgradient-based neurodynamic approach with projection operator to achieve the optimal power consumption of intelligent and connected vehicles. By differential inclusion and nonsmooth analysis, it is confirmed that the state solution of neurodynamic system converges to the optimal solution of the distributed optimization problem. With the help of the algorithm, all intelligent and connected vehicles asymptotically reach a consensus on an optimal power consumption. Simulation results show that the proposed neurodynamic approach is capable of effectively solving the problem of power consumption optimal control for intelligent and connected vehicles cooperative system.