对分数阶非线性悬架的遗传优化PI~λD~μ控制
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摘要
针对由分数阶磁流变阻尼和非线性弹簧组成的复杂车辆悬架系统进行减振控制研究。首先建立1/4车辆二自由度非线性悬架数学模型,然后结合分数阶微积分理论,设计PI~λD~μ控制器,采用遗传算法在线整定分数阶PID控制器参数,其中以车身垂直加速度、悬架动位移和轮胎动变形为优化指标建立适应度函数。同时在Matlab/Simulink中对非线性悬架分别进行分数阶PID控制、整数阶PID控制与被动悬架的性能对比仿真实验。结果表明,以遗传算法在线整定的分数阶PID控制器与被动悬架和整数阶PID控制的悬架相比减振效果更好,说明在既含有分数阻尼器又含有非线性弹簧时,其对悬架进行控制是有效的。
Vibration damping control of a complex vehicle suspension system consisting of fractional order MRF damping and nonlinear spring is studied. Firstly,the 1/4 vehicle two degree of freedom nonlinear suspension mathematical model is established,and then combined with the fractional calculus theory,the PID controller is designed. The genetic algorithm is used to adjust the parameters of fractional PID controller online,in which the vertical acceleration,suspension dynamic displacement and tire dynamic deformation are taken as the optimization indexes to establish fitness function. At the same time,the performance simulation experiments of fractional order PID control,integer order PID control and passive control for nonlinear suspension are carried out in Matlab/Simulink. The results show that the fractional order PID controller with online tuning of genetic algorithm is better than passive suspension and integer PID control. It shows that it is effective to control the suspension when both fractional dampers and nonlinear springs are included.
Vibration damping control of a complex vehicle suspension system consisting of fractional order MRF damping and nonlinear spring is studied. Firstly,the 1/4 vehicle two degree of freedom nonlinear suspension mathematical model is established,and then combined with the fractional calculus theory,the PID controller is designed. The genetic algorithm is used to adjust the parameters of fractional PID controller online,in which the vertical acceleration,suspension dynamic displacement and tire dynamic deformation are taken as the optimization indexes to establish fitness function. At the same time,the performance simulation experiments of fractional order PID control,integer order PID control and passive control for nonlinear suspension are carried out in Matlab/Simulink. The results show that the fractional order PID controller with online tuning of genetic algorithm is better than passive suspension and integer PID control. It shows that it is effective to control the suspension when both fractional dampers and nonlinear springs are included.
引文
[1]冯霏,刘杨,李凌轩,等.汽车非线性悬架最优控制的研究[J].中国工程机械学报,2010,8(2):143-146.
[2]岳书常.汽车悬架系统非线性振动最优控制研究[D].淄博:山东理工大学,2016.
[3]刘晓梅,李洪友,黄宜坚.磁流变阻尼器的分数阶Bingham模型研究[J].机电工程,2015,32(3):338-342.
[4]陈炎冬.对含分数阶阻尼器非线性悬架的PID控制研究[J].机械制造与自动化,2016,45(6):88-91.
[5]孔祥东,李斌,权凌霄,等.磁流变液阻尼器Bingham-多项式力学模型研究[J].机械工程学报,2017,53(14):179-186.
[6] SHAH P,AGASHE S. Review of fractional PID controller[J]. Mechatronics,2016(38):29-41.
[7] REYAD El-Khazali. Fractional-order PIλDμcontroller design[J]. Pergamon Press,Inc,2013,66(5):639-646.
[8]蓝会立,高远,周晓华.汽车非线性悬架的最优分数阶PIλDμ控制[J].广西科技大学学报,2015,26(4):42-48.
[9]彭建伟,周建斌,柳向斌.分数阶PIλDδ控制器的设计[J].制造业自动化,2010,32(15):35-36,52.
[10] DAS S,PAN I,DAS S,et al. Improved model reduction and tuning of fractional-order PI(λ)D(μ)controllers for analytical rule extraction with genetic programming[J]. Isa Transactions,2012,51(2):237-261.
[11]孟杰,杨海鹏,陈庆樟,等.基于遗传算法优化的汽车半主动悬架PID控制仿真研究[J].现代制造工程,2013,(6):92-96.
[12] GAD S,METERED H,BASSUINY A,et al. Multi-objective genetic algorithm fractional-order PID controller for semiactive magnetorheologically damped seat suspension[J].Journal of Vibration&Control,2016(34):71-80.
[13]齐乃明,秦昌茂,王威.分数阶系统的最优Oustaloup数字实现算法[J].控制与决策,2010,25(10):1598-1600.
[14]郑玲,牛伯瑶,李以农,等.基于遗传算法的汽车磁流变减振器多目标优化[J].汽车工程,2016,38(7):871-877.
[15]梁永勤,毕凤荣,石纯放.基于遗传算法的麦弗逊悬架参数优化研究[J].机械设计,2017,34(1):15-19.
[16]陈杰平,陈无畏,祝辉,等.基于Matlab/Simulink的随机路面建模与不平度仿真[J].农业机械学报,2010,41(3):11-15.
[17]于曰伟,周长城,赵雷雷,等.基于交替迭代的车辆主动悬架LQG控制器设计[J].山东大学学报(工学版),2017,47(4):50-58.
[2]岳书常.汽车悬架系统非线性振动最优控制研究[D].淄博:山东理工大学,2016.
[3]刘晓梅,李洪友,黄宜坚.磁流变阻尼器的分数阶Bingham模型研究[J].机电工程,2015,32(3):338-342.
[4]陈炎冬.对含分数阶阻尼器非线性悬架的PID控制研究[J].机械制造与自动化,2016,45(6):88-91.
[5]孔祥东,李斌,权凌霄,等.磁流变液阻尼器Bingham-多项式力学模型研究[J].机械工程学报,2017,53(14):179-186.
[6] SHAH P,AGASHE S. Review of fractional PID controller[J]. Mechatronics,2016(38):29-41.
[7] REYAD El-Khazali. Fractional-order PIλDμcontroller design[J]. Pergamon Press,Inc,2013,66(5):639-646.
[8]蓝会立,高远,周晓华.汽车非线性悬架的最优分数阶PIλDμ控制[J].广西科技大学学报,2015,26(4):42-48.
[9]彭建伟,周建斌,柳向斌.分数阶PIλDδ控制器的设计[J].制造业自动化,2010,32(15):35-36,52.
[10] DAS S,PAN I,DAS S,et al. Improved model reduction and tuning of fractional-order PI(λ)D(μ)controllers for analytical rule extraction with genetic programming[J]. Isa Transactions,2012,51(2):237-261.
[11]孟杰,杨海鹏,陈庆樟,等.基于遗传算法优化的汽车半主动悬架PID控制仿真研究[J].现代制造工程,2013,(6):92-96.
[12] GAD S,METERED H,BASSUINY A,et al. Multi-objective genetic algorithm fractional-order PID controller for semiactive magnetorheologically damped seat suspension[J].Journal of Vibration&Control,2016(34):71-80.
[13]齐乃明,秦昌茂,王威.分数阶系统的最优Oustaloup数字实现算法[J].控制与决策,2010,25(10):1598-1600.
[14]郑玲,牛伯瑶,李以农,等.基于遗传算法的汽车磁流变减振器多目标优化[J].汽车工程,2016,38(7):871-877.
[15]梁永勤,毕凤荣,石纯放.基于遗传算法的麦弗逊悬架参数优化研究[J].机械设计,2017,34(1):15-19.
[16]陈杰平,陈无畏,祝辉,等.基于Matlab/Simulink的随机路面建模与不平度仿真[J].农业机械学报,2010,41(3):11-15.
[17]于曰伟,周长城,赵雷雷,等.基于交替迭代的车辆主动悬架LQG控制器设计[J].山东大学学报(工学版),2017,47(4):50-58.