为了实现高速列车对目标速度轨迹的精确跟踪,提出了一种不依赖于模型参数和附加阻力信息的列车鲁棒自适应速度跟踪控制算法.首先,将列车模型参数分解为标称值和参数不确定性两部分,并将由参数不确定性和附加阻力引起的不确定性看作系统的集总不确定性;其次,引入带σ修正的参数自适应更新律对模型参数标称值及系统集总不确定性的上界进行在线估计,并在控制律中引入鲁棒项以补偿系统的集总不确定性;最后,基于Lyapunov稳定性理论和数值仿真验证了算法的可行性和有效性.研究结果表明,在模型参数和附加阻力信息未知的情况下,该控制算法实现了列车运行过程对目标轨迹的精确跟踪,且对模型参数和附加阻力的时变不确定性具有很强的鲁棒性.
In order to realize the accurate velocity tracking of high-speed trains to the target trajectory,a robust a-daptive velocity tracking control algorithm for trains independent of model parameters and additional resistance in-formation is proposed.Firstly,the parameters of train model are decomposed into nominal values and parameter un-certainties,and the uncertainty caused by parameter uncertainties and additional resistance is regarded as the lumped uncertainty of the system.Then,adaptive updating laws for the nominal values of model parameters and the upper bound of the system lumped uncertainty are designed based on σ-modification adaptive technique,and a ro-bust term is introduced into the control law to compensate for the system lumped uncertainty.Finally,the feasibility and effectiveness of the algorithm are verified based upon Lyapunov stability theory and numerical simulation.The research results show that the control algorithm can achieve accurate tracking to the target trajectory during the train operation even if the information of model parameters and additional resistance is unknown,with strong robustness to the time-varying uncertainties of model parameters and additional resistance.