Research On Multi-Objective Whale Optimization And Predictive Function Control Algorithms For Velocity Curve Of Urban Rail Vehicle

The urban rail transit system with automatic train operation system has the advantages of safety,stability,economy,energy efficiency and comfort,and it has become one of the research hot spots of the urban transportation.Multiple performance indicators such as energy saving,comfort,punctuality and accurate parking shoule be optimized as much as possible.This not only focus on perfect performance of ATO system optimizer which obtain the target velocity curve with multiple prospective performance indicators as optimal as possible,but also necessary to aware of the tracking controller of ATO system to track control according to target velocity curve accurate and stable.However,aiming at the problem of easy to fall into local convergence for traditional improved target velocity curve optimization algorithms,it is necessary to improve the traditional tracking control algorithm for target velocity curve in urban rail vehicle further to improve its multi-objective comprehensive performance quality.The main research works of this dissertation are as follows.Firstly,aiming at the optimization problem for velocity curve of urban rail vehicle,an improved multi-objective whale optimization algorithm based on angle penalized distance IWOA-APD is proposed.Based on led step weight into basic whale optimization algorithm,a kind of nonlinear decreasing strategies of convergence factor and step weight based on iteration progressand optimization factors is given,and these strategies can further improve the optimization performance by using optimization factors.In addition,the comprehensive learning strategy,the improved elite set maintenance mechanism and the two populations migration mechanism based on fusion distance are integrated into the IWOA-APD.As can be seen the optimization results obtained by Matlab/Simulink and HIL simulations,compared with several algorithms with better optimization performance in the literature,the IWOA-APD can improve optimization effect significantly.Secondly,based on IWOA-APD,an improved multi-objective whale optimization algorithm based on angle penalized distance using minimum preference angle cosine IWOA-PAPD is proposed.By leading into minimum preference angle cosine,the angle penalized distance using minimum preference angle cosine PAPD is given.It can solve the preference multi-objective optimization problem effectively.As can be seen the optimization results obtained by Matlab/Simulink and HIL simulations,compared with several algorithms with better optimization performance in the literature,the IWOA-PAPD has significantly improved optimization effect for preference multi-objective optimization problem.Finally,aiming at the tracking control problem for velocity curve of urban rail vehicle,an improved predictive function control algorithm IPFC is proposed.Based on the analysis of the influence of softening factor on control performance in predictive functional control,an adaptive nonlinear online softening factor adjustment strategy based on fuzzy satisfaction of system performance and optimization factor is proposed,and this strategy can further improve the tracking control performance by using optimization factor.According to the change degree of target velocity curve,a strategy for basis function selection of predictive function control is given,which can switch wavelet and step basis function.In addition,the optimized control parameters can be set.As can be seen the tracking control results obtained by Matlab/Simulink and HIL simulations,compared with several algorithms with better control performance in the literature,the IPFC can improve control performance of control system significantly.Aiming at verifing the effectiveness of the proposed multi-objective optimization and control algorithms for velocity curve of urban rail vehicle more effectively,a hardware in the loop simulation platform including optimizer,conditioning circuit,signal processing unit and other real on-board equipments is designed and built.Under hardware in the loop simulation platform,based on a specific scene(from Lvshun New Port to Tieshan Town in Dalian urban rail transit line 12),the proposed and several traditional algorithms are implemented.The simulation results further verify the effectiveness.