Affiliations:
School of Electrical Engineering, Beijing Jiaotong University, Beijing, P. R. China
Correspondence:
[*]
Corresponding author. Lide Wang, Professor, Beijing Jiaotong University, P. R. China. E-mail: ldwang@bjtu.edu.cn.
Note: [1] This work is supported by the Research and Development Plan of Science and Technology for China Railway Corporation (2015J011-F) and the Fundamental Research Funds for the Central Universities (2014JBM113).
Abstract: This paper addresses the scheduling problem of periodic information in multifunction-vehicle-bus networked control system (MNCS). To deal with this issue, a novel fuzzy immune particle swarm optimization (FIPSO) algorithm is proposed to eliminate the premature convergence of standard PSO algorithms in solving complex problem, which uses the fuzzy particle swarm optimization (FPSO) algorithm and the immune particle swarm optimization (IPSO) algorithm for reference. Through designing the fuzzy logic controller (FLC), the inertia weight and the immune-execute factor are regulated dynamically on the basis of the evolutionary time, the variation of average fitness value and the population diversity. The FLC also guides evolutionary directions and decides whether to execute immune operations, making the algorithm converge for many times. The simulation and calculation results of the scheduling example show that FIPSO algorithm has strong global search ability, good stability and better optimization performance. Particularly, based on the variable individual periods, the co-design of scheduling and control in MNCS is implemented by applying the FIPSO algorithm.
Keywords: Particle swarm optimization, multifunction vehicle bus (MVB), scheduling, networked control system (NCS), co-design
