Study On Coordinated Predictive Control Of Suspension System Of Hybrid Multi-Magnet Maglev Train

As the high-speed railway has gradually become the hotspot of the world’s transportation development,maglev train technology has emerged as the times require.Maglev trains are fast,efficient,convenient,and environmentally friendly,and are the development trend of high-speed trains in the future.The quality of levitation control technology is the prerequisite for determining the smooth operation of a maglev train.Therefore,it is of great significance to improve the performance of the levitation control system.At present,there have been certain researches on the levitation control algorithm of pure electromagnet maglev trains at home and abroad,but there are few researches on electromagnetic permanent-magnet hybrid suspension systems.Compared with pure electromagnetic suspension,hybrid suspension has lower energy consumption and fewer construction difficulty and cost.For levitation control algorithms,model predictive control has a strong ability to deal with constrained control problems,and it has well developed.At present,most levitation control systems either select a single electromagnet without considering the coupling effects,or select the entire levitation modules for decoupling,but these research solutions do not consider the coordination relationship between the modules,which is not conducive to the improvement of the overall performance of the system.Therefore,this thesis takes the electromagnetic permanent-magnet hybrid maglev train as the research object,and conducts the research on the coordinated predictive control algorithm of the train levitation system.The main research is described as follows:(1)According to the characteristics of the nonlinear model of a single-magnet hybrid levitation system,a hybrid multi-magnet levitation nonlinear model based on voltage control is established.The stability of the model is analyzed employing the theory of nonlinear control system,and the MATLAB/Simulink tool is used to simulate and verify the instability of the model.(2)On the basis of the hybrid suspension model,the cross-coupling method is applied to coordinate and control the two ends of the suspension modules,and the factors that affect the synchronization performance are analyzed.The MATLAB/Simulink tool is used to analyze the status in case of disturbances and parameter mismatches.(3)On the basis of multi-magnet coordination,the model predictive control method is adopted to design the unconstrained predictive controller of a hybrid multi-magnet suspension system.By adding the disturbances such as simulated sudden loads and uneven track surfaces,the performance of the predictive controller is analyzed,and its control ability is simulated and verified.To further improve the control performance,the system state variables and control variables are constrained,and a constraint predictive controller is designed,and the path tracking interior-point method is chosen to solve the problem.The potential shortcomings of the interior-point method are analyzed,and a particle swarm optimization algorithm with better performance is employed.A particle swarm intelligent optimization algorithm is designed to solve the constrained model predictive controller using the penalty function method to deal with constraints.(4)The feasibility and effectiveness of the designed control algorithm are verified by MATLAB simulation.The simulation results show that the constraint coordinated predictive controller based on particle swarm optimization has good control effects,and can well meet the requirements of multiple constraints,real-time performance and anti-disturbance performance for the maglev train suspension.55 Pictures,6 Tables,56 References.