基于人工免疫算法的EPS控制算法及其仿真研究
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摘要
电动助力转向系统(Electric Power Steering,简称EPS)是一种机电一体化的新型智能助力转向系统。它兼顾了车辆在低速转向时的轻便性和高速转向时的良好路感,改善了车辆行驶过程中的操作稳定性。EPS与以往的转向系统相比,具有更高的安全性和灵活性,还拥有节能环保、结构简单,易于安装等优势,从而成为现代汽车转向系统开发和研究的热点。
在本论文中,首先介绍电动助力转向系统的工作原理、基本结构和常用的转向系统建模方法。然后在参考相关文献的基础上,利用降阶法建立了简化的电动助力转向系统模型,并与二自由度的汽车模型结合构成含有EPS的汽车模型。在此之上,利用Lyapunov稳定性理论,通过构造相应的Lyapunov函数,分析所建电动助力转向系统模型的稳定性。
其次,介绍电动助力转向系统常用的控制方法和控制策略。着重分析EPS的助力特性及其转向的助力曲线,研究基于智能PID的电动助力转向助力控制算法,提出基于免疫反馈PID控制算法的控制策略,进行仿真实验,并将该算法与遗传算法对EPS的控制参数优化进行比较,说明算法的有效性。
然后,本文借助与实车系统相当接近的商业化仿真软件CARSIM,进一步验证所建立电动助力转向系统模型的可靠性及免疫算法对EPS控制参数优化的可行性。在CARSIM中对整车及仿真工况参数进行设定,同时在MATLAB/Simulink中建立EPS仿真模型,从而实现两个软件的联合仿真。在相同工况下,将建立的带有EPS的整车模型与带有液压助力转向系统的整车模型相比,实验结果表明,所建立的电动助力转向系统模型具有良好的可靠性和助力性。用免疫反馈PID控制策略与遗传PID策略对助力电机电流进行控制仿真,结果表明采用免疫反馈PID算法控制下的EPS转向更加轻便、平稳,从而验证免疫反馈PID控制策略用于EPS控制上是行之有效的。
最后,对本文进行总结,并针对该系统提出一些尚待进一步研究的问题,为今后的继续研究工作确定方向。
Electric Power Steering system (abbr. EPS) is a new kind of mechatronics and intelligence power steering system. It meets the requirements of vehicle low-move steering portability and high-move road feeling, and improves the system handling performance. Compare with the traditional steering systems, EPS has some advantages in engine efficiency, environmental protection, safety, flexibility, simple structure, and easy installation.As a result, EPS is becoming the development and the research hot pot of modern vehicle’s steering system.
This paper first introduced the working principle, structure of EPS, as well as the general methods of building steering system model. Then according to the relevance literatures, the simplified model of EPS established by the order reduction method, combining with a vehicle model of two degrees of freedom constitutes the full vehicle system equipped with EPS. According to Lyapunov stability theory, the stability of EPS mentioned above was analyzed by constructing the Lyapunov function.
Secondly, the control algorithm and strategy of EPS were addressed. The assistant characteristics and curves were emphatically analyzed. Immune-feedback-PID control strategy was put forward and designed to control EPS, based on intelligence-PID of assistance control for EPS. The test results showed that immune-feedback-PID control strategy, compared with genetic algorithm, is more efficiency on account of optimization for control parameters.
Thirdly, in order to verify the algorithm mentioned above, whose correctness of EPS model and validity of EPS optimization the control parameters equipped with immune algorithm were further validated, the commercial software-CARSIM closing to the actual vehicle was employed. The Co-simulation technology was used through CARSIM and MATLAB/Simulink, in CARSIM, vehicle parameters and simulation condition were set, and in MATLAB/Simulink, EPS simulation model was established. Under the same conditions, the results of simulation and test prove that the vehicle model equipped with the EPS has good reliability and assistant characteristics, compared with the vehicle model with the hydraulic power steering system.Two methods were brought forward during simulation and test in controlling current assist motor. One is immune-feedback-PID control; the other is PID algorithm control. The simulation results show that EPS using immune-feedback-PID control strategy is more lightweight, stable, which is effective to control EPS.
Finally, the main work of this thesis was summed up,and the shortcomings of thesis and the prospects of the future work was introduced, which determine the future working direction.
在本论文中,首先介绍电动助力转向系统的工作原理、基本结构和常用的转向系统建模方法。然后在参考相关文献的基础上,利用降阶法建立了简化的电动助力转向系统模型,并与二自由度的汽车模型结合构成含有EPS的汽车模型。在此之上,利用Lyapunov稳定性理论,通过构造相应的Lyapunov函数,分析所建电动助力转向系统模型的稳定性。
其次,介绍电动助力转向系统常用的控制方法和控制策略。着重分析EPS的助力特性及其转向的助力曲线,研究基于智能PID的电动助力转向助力控制算法,提出基于免疫反馈PID控制算法的控制策略,进行仿真实验,并将该算法与遗传算法对EPS的控制参数优化进行比较,说明算法的有效性。
然后,本文借助与实车系统相当接近的商业化仿真软件CARSIM,进一步验证所建立电动助力转向系统模型的可靠性及免疫算法对EPS控制参数优化的可行性。在CARSIM中对整车及仿真工况参数进行设定,同时在MATLAB/Simulink中建立EPS仿真模型,从而实现两个软件的联合仿真。在相同工况下,将建立的带有EPS的整车模型与带有液压助力转向系统的整车模型相比,实验结果表明,所建立的电动助力转向系统模型具有良好的可靠性和助力性。用免疫反馈PID控制策略与遗传PID策略对助力电机电流进行控制仿真,结果表明采用免疫反馈PID算法控制下的EPS转向更加轻便、平稳,从而验证免疫反馈PID控制策略用于EPS控制上是行之有效的。
最后,对本文进行总结,并针对该系统提出一些尚待进一步研究的问题,为今后的继续研究工作确定方向。
Electric Power Steering system (abbr. EPS) is a new kind of mechatronics and intelligence power steering system. It meets the requirements of vehicle low-move steering portability and high-move road feeling, and improves the system handling performance. Compare with the traditional steering systems, EPS has some advantages in engine efficiency, environmental protection, safety, flexibility, simple structure, and easy installation.As a result, EPS is becoming the development and the research hot pot of modern vehicle’s steering system.
This paper first introduced the working principle, structure of EPS, as well as the general methods of building steering system model. Then according to the relevance literatures, the simplified model of EPS established by the order reduction method, combining with a vehicle model of two degrees of freedom constitutes the full vehicle system equipped with EPS. According to Lyapunov stability theory, the stability of EPS mentioned above was analyzed by constructing the Lyapunov function.
Secondly, the control algorithm and strategy of EPS were addressed. The assistant characteristics and curves were emphatically analyzed. Immune-feedback-PID control strategy was put forward and designed to control EPS, based on intelligence-PID of assistance control for EPS. The test results showed that immune-feedback-PID control strategy, compared with genetic algorithm, is more efficiency on account of optimization for control parameters.
Thirdly, in order to verify the algorithm mentioned above, whose correctness of EPS model and validity of EPS optimization the control parameters equipped with immune algorithm were further validated, the commercial software-CARSIM closing to the actual vehicle was employed. The Co-simulation technology was used through CARSIM and MATLAB/Simulink, in CARSIM, vehicle parameters and simulation condition were set, and in MATLAB/Simulink, EPS simulation model was established. Under the same conditions, the results of simulation and test prove that the vehicle model equipped with the EPS has good reliability and assistant characteristics, compared with the vehicle model with the hydraulic power steering system.Two methods were brought forward during simulation and test in controlling current assist motor. One is immune-feedback-PID control; the other is PID algorithm control. The simulation results show that EPS using immune-feedback-PID control strategy is more lightweight, stable, which is effective to control EPS.
Finally, the main work of this thesis was summed up,and the shortcomings of thesis and the prospects of the future work was introduced, which determine the future working direction.
引文
[1]王勇.汽车电动助力转向系统动力学分析与仿真[D]:重庆:重庆交通大学车辆工程系,2008
[2]徐建平.电动助力转向系统设计和分析[D]:江苏:江苏大学车辆工程系,2004
[3]徐中兴.汽车的电动助力转向系统[D]:南昌:南昌大学软件工程系,2009
[4]任宏涛,崔凤奎.基于遗传算法的电动助力转向系统结构参数优化设计[J].洛阳理工学院学报(自然科学版),2009.19(1):42～46
[5]胡爱军,林逸,施国标.电动助力转向系统结构参数优化[J].拖拉机与农用运输车,2008.35 (5):38～42
[6]刘照,杨家军,廖道训.基于混合灵敏度方法的电动助力转向系统控制[J].中国机械工程, 2003.14(10):874～876
[7]王其东,杨孝剑,陈无畏,等.电动助力转向系统的建模及控制[J].农业机械学报,2004. 35(5):1～5
[8]郭孔辉,轧浩,宗长富.横摆角速度反馈汽车转向控制的理论研究[J].中国机械工程,2000. 11(2):61～64
[9]任卫群,陈慧鹏,谢彬,等.电动助力转向系统对汽车操纵稳定性的影响[J].华中科技大学学报(自然科学版),2008.36(9):83～87
[10]何仁,徐建平.电动助力转向系统稳定性分析[J].江苏大学学报(自然科学版),2004. 25 (4):294～297
[11] Carter J h. The immune system as a model for pattern recognition and classification [J].Journal of the American Medical Informatics Association, 2000.7(1):28～41
[12] Castiglione F, Motta S, Nicosia G. Pattern recognition by recognition by primary and secondary response of an artificial immune system[J]. Theory in Biosciences, 2001.120(2):93～106
[13] White J A, Garrett S M. Improved pattern recognition with artificial clonal selection [J].Lecture Notes in Computer Science, 2003.181～193
[14] Gong M G, Du H F, Jiao L C et al. Immune clonal selection algorithm for multiuser detection in DS-CDMA systems [J].Lecture Notes in Artificial Intelligence, 2004.1219～1225
[15] Aickelin U,Greensmith J,Twycross J. Immune system approaches to intrusion detection-a review[J].Lecture Notes in Computer Science,2004.316～329
[16] Ishiguro A,Kuboshiki S,Ichikawa S.Gait Control of hexapod walking robots using mutual-coupled immune networks[J].Advanced Robotics,1996.10(2):179～195
[17] Chun J S, Kim M K,Jung H K et al. Shape optimization of electromagnetic devices using immune algorithm[J].IEEE Transactions on Magnetics,1997.33(2):295～308
[18] Aguilar J. An artificial immune system for fault detection[J].Lecture Notes in Artificial Intellifence,2004.219～228
[19] Canham R O.Tyrrell A M. A hardware artificial immune system and embryonic array for fault tolerant systems[J].Genetic Programming an Evolvable Machines, 2003.4(4):359～382
[20] Frcschi F, Repetto M. Multiobjective optimization by a modified artificial immune system algorithm[J]. Lecture Notes in Computer Science,2005. 248～261
[21] Coello C A C, Cortes N C.Hybridizing a genetic algorithm with an artificial immune system for global optimization[J]. Engineering Optimization,2004. 36(5):607～634
[22]莫宏伟,吕淑萍,管凤旭等.基于人工免疫系统的数据挖掘技术原理与应用[J].计算机工程与应用,2004.40(14):28～33
[23] Alves R T, Delgado M R, Lopes H S et al. An artificial immune system for fuzzy-rule induction in data mining[J]. Lecture Notes in Computer Science,2004. 1011～1020
[24]谭光兴,杜启亮,毛宗源.基于克隆选择的锌钡白煅烧过程数据挖掘[J].计算机工程与应用, 2006.42(35):211～213,218
[25]丁永生,任立红.一种新颖自调节免疫反馈控制系统[J].控制与决策,2000.15(4)443～446
[26] Karr C L, Nishita K, Graham K S. Adaptive aircraft flight control simulation based on an artificial immune system[J]. Applied Intelligence, 2005.23(3):295～308
[27] Takahashi,K.,Yamada,T.Application of all Immune Feedback Mechanism to Control Systems[J].JSME International Joumal,Series C,1998,41(2):184～191
[28]付冬梅,郑德玲,位耀光,等.人工免疫控制器的设计及其控制效果的仿真[J].北京科技大学学报,2004.26(4):442～445
[29]唐旭东,庞永杰,李晔.基于S模型的水下机器人改进人工免疫控制器[J].大连海事大学学报,2008.34(1):50～53
[30]庞永杰,唐旭东.改进人工免疫算法在水下机器人运动控制中的应用研究[J].计算机应用研究,2008.25(9):2640～2642
[31]刘国联,谭冠政,何燕.基于改进人工免疫算法的PID参数优化研究[J].计算机工程与应用, 2008.44(19):84～86
[32]廖亦凡.机械臂液压驱动系统设计与模糊免疫PID控制策略研究[D]:长沙:湖南师范大学电路与系统,2006
[33]王强,钱敏,陈军,等.改进型免疫算法PID设计及在调速系统中的应用[J].电气传动, 2009.39(2):56～60
[34]冯冬青,张志娟.预估模糊免疫PID在房问温度控制中的应用[J].计算机工程与设计,2009. 30(19):4479～4482.
[35]陈少白,谭光兴,毛宗源.基于一种人工免疫算法的PID参数优化[J].武汉科技大学学报, 2006.29(3):313～315
[36]左兴权,李士勇.一种基于人工免疫原理的最优模糊神经网络控制器[J].信息与控制,2004. 33(3):380～385
[37]夏长亮,刘丹,王迎发.无刷直流电机免疫反馈自适应学习人工神经网络控制[J].天津大学学报,2007.40(10):1235～1240
[38] Lee D W .Sim K B.Artificial Immune Network—based Cooperative Control in Collective Autonomous Robots[C] . In : Proc 6th IEEE Int Workshop on Robot and Human Communication Sendai.1997.58～63
[39] Kumak K K.Neidhoefer J.Immunized Neurocontro1[J]. Expert Systems with Applications, l997.13(3):2Ol～214
[40]黄亚玲,贾红红.汽车转向技术发展综述[J].民营科技,2009.6:1,120
[41]臧怀泉,刘敏.EPS参数的优化设计及仿真[J].辽宁工程技术大学学报,2008.27(1):76～78
[42] W.Keith Adams, Richard W.Topping.The Steering Characterizing Functions (SCFs) and Their Use in Steering System Specification,Simulation, and Synthesis.
[43] M.Kamel Salaani. Modeling and Implementation of Steering System Feedback for the National Advanced Driving Simulator.SAE.2002
[44]许洪国.汽车理论[M].北京:人民交通出版社,2008
[45]郭孔辉.轮胎侧偏特性的一般理论模型[J].汽车工程,1990.3:1～12
[46]李伟,刘晓.汽车电动助力转向系统特性研究[J].客车技术与研究,2005.4:1～5
[47]李强.基于分岔理论的电动助力转向系统控制策略及其对汽车操纵稳定性影响的研究[D]:江苏:江苏大学车辆工程系,2007
[48]段广仁.线性系统理论[M].哈尔滨:哈尔滨工业大学出版社,2002
[49]唐子雷.汽车电动助力转向电子控制系统的研究[J].机械管理开发,2007.4:10～12
[50]雷明森,向铁明.汽车电动助力转向的控制策略[J].公路与汽运,2008.7(4):20～22
[51]张春花,李翔晟,肖朝明.电动助力转向系统控制策略研究[J].自动化技术与应,2007.26 (2):30～32
[52]曾群.纯电动汽车电动助力转向系统机理研究与设计[D]:南昌:南昌大学机械电子工程, 2009
[53]黄李琴,季学武,陈奎元.汽车电动助力转向控制系统的初步研究[J].汽车技术,2003.6:3～6
[54]刘慧忱.汽车电动助力转向系统控制规律的研究[D]:重庆:重庆交通大学车辆工程系,2007
[55]刘鹏,姚艳.电动助力转向系统的PID控制及仿真研究[J].机械与电子,2008.(3):41～44
[56]卢娟.电动助力转向系统建模与仿真研究[D]:重庆:重庆大学车辆工程,2006
[57]周冬林,黄菊花,曾群.基于电动助力转向系统控制算法的研究[J].计算技术与自动化,2009.28(1):80～83
[58]刘俊,陈无畏.车辆电动转向系统的卡尔曼滤波模糊PID控制[J].农业机械学报,2007.38 (9):1～5
[59]高明,朱懿韬,许南绍.基于转向盘转动速度变转矩控制的电动助力转向系统[J].重庆工学院学报,2009.23(2):7～12
[60]王柏峰,钟勇,李志强,等.基于径向基神经网络的EPS助力控制方法[J].客车技术与研究,2007.4:12～15
[61]刘照.汽车电动助力转向系统动力学分析与控制方法研究[D]:武汉:华中科技大学机械设计及理论,2004
[62]吴勃夫.基于预测控制的汽车主动悬架与电动助力转向系统集成控制优化设计[D]:合肥:合肥工业大学车辆工程系,2006
[63]王其东,吴勃夫,陈无畏.基于预测控制的主动悬架与电动助力转向集成控制[J].农业机械学报,2007.38(1):1～5
[64]王其东,秦炜华,陈无畏.基于多自由度模型的汽车ASS与EPS集成控制研究[J].系统仿真学报,2009.21(16):5130～5134
[65]蔡自兴.智能控制原理与应用[M].北京:新华大学出版社,2007
[66]李娜,仁庆道尔吉.车间作业调度及其遗传算法[J].内蒙古工业大学学报,2009.1(2):21～26
[67]莫宏伟.人工免疫系统原理与应用[M].哈尔滨:哈尔滨工业大学出版,2003
[68]张乐,陆金桂.改进的免疫算法求解TSP问题[J].计算机工程与应用,2005.87～88.
[69]谭光兴,毛宗源.一种基于模仿者动态模型的免疫算法[J].计算机工程与应用,2006.42 (2):55～57,190
[70]谭光兴,毛宗源,何元烈.一种基于抗体网络的免疫算法[J].计算机工程与设计,2007.28 (5):1104～1107
[71]王康康,唐岚,黎长青.基于AMESim和Simulink的汽车电动助力转向系统的联合仿真,机床与液压[J].2008,6.36(6):107～109
[72] Mechamical Simulation Corporation, Ann Arbor,MI USA.MSC CARSIM User Mannual (version8),2008
[73]冯广刚.基于主被动集成的汽车安全控制系统建模与仿真[D]:湖南:湖南大学车辆工程专业,2008
[2]徐建平.电动助力转向系统设计和分析[D]:江苏:江苏大学车辆工程系,2004
[3]徐中兴.汽车的电动助力转向系统[D]:南昌:南昌大学软件工程系,2009
[4]任宏涛,崔凤奎.基于遗传算法的电动助力转向系统结构参数优化设计[J].洛阳理工学院学报(自然科学版),2009.19(1):42～46
[5]胡爱军,林逸,施国标.电动助力转向系统结构参数优化[J].拖拉机与农用运输车,2008.35 (5):38～42
[6]刘照,杨家军,廖道训.基于混合灵敏度方法的电动助力转向系统控制[J].中国机械工程, 2003.14(10):874～876
[7]王其东,杨孝剑,陈无畏,等.电动助力转向系统的建模及控制[J].农业机械学报,2004. 35(5):1～5
[8]郭孔辉,轧浩,宗长富.横摆角速度反馈汽车转向控制的理论研究[J].中国机械工程,2000. 11(2):61～64
[9]任卫群,陈慧鹏,谢彬,等.电动助力转向系统对汽车操纵稳定性的影响[J].华中科技大学学报(自然科学版),2008.36(9):83～87
[10]何仁,徐建平.电动助力转向系统稳定性分析[J].江苏大学学报(自然科学版),2004. 25 (4):294～297
[11] Carter J h. The immune system as a model for pattern recognition and classification [J].Journal of the American Medical Informatics Association, 2000.7(1):28～41
[12] Castiglione F, Motta S, Nicosia G. Pattern recognition by recognition by primary and secondary response of an artificial immune system[J]. Theory in Biosciences, 2001.120(2):93～106
[13] White J A, Garrett S M. Improved pattern recognition with artificial clonal selection [J].Lecture Notes in Computer Science, 2003.181～193
[14] Gong M G, Du H F, Jiao L C et al. Immune clonal selection algorithm for multiuser detection in DS-CDMA systems [J].Lecture Notes in Artificial Intelligence, 2004.1219～1225
[15] Aickelin U,Greensmith J,Twycross J. Immune system approaches to intrusion detection-a review[J].Lecture Notes in Computer Science,2004.316～329
[16] Ishiguro A,Kuboshiki S,Ichikawa S.Gait Control of hexapod walking robots using mutual-coupled immune networks[J].Advanced Robotics,1996.10(2):179～195
[17] Chun J S, Kim M K,Jung H K et al. Shape optimization of electromagnetic devices using immune algorithm[J].IEEE Transactions on Magnetics,1997.33(2):295～308
[18] Aguilar J. An artificial immune system for fault detection[J].Lecture Notes in Artificial Intellifence,2004.219～228
[19] Canham R O.Tyrrell A M. A hardware artificial immune system and embryonic array for fault tolerant systems[J].Genetic Programming an Evolvable Machines, 2003.4(4):359～382
[20] Frcschi F, Repetto M. Multiobjective optimization by a modified artificial immune system algorithm[J]. Lecture Notes in Computer Science,2005. 248～261
[21] Coello C A C, Cortes N C.Hybridizing a genetic algorithm with an artificial immune system for global optimization[J]. Engineering Optimization,2004. 36(5):607～634
[22]莫宏伟,吕淑萍,管凤旭等.基于人工免疫系统的数据挖掘技术原理与应用[J].计算机工程与应用,2004.40(14):28～33
[23] Alves R T, Delgado M R, Lopes H S et al. An artificial immune system for fuzzy-rule induction in data mining[J]. Lecture Notes in Computer Science,2004. 1011～1020
[24]谭光兴,杜启亮,毛宗源.基于克隆选择的锌钡白煅烧过程数据挖掘[J].计算机工程与应用, 2006.42(35):211～213,218
[25]丁永生,任立红.一种新颖自调节免疫反馈控制系统[J].控制与决策,2000.15(4)443～446
[26] Karr C L, Nishita K, Graham K S. Adaptive aircraft flight control simulation based on an artificial immune system[J]. Applied Intelligence, 2005.23(3):295～308
[27] Takahashi,K.,Yamada,T.Application of all Immune Feedback Mechanism to Control Systems[J].JSME International Joumal,Series C,1998,41(2):184～191
[28]付冬梅,郑德玲,位耀光,等.人工免疫控制器的设计及其控制效果的仿真[J].北京科技大学学报,2004.26(4):442～445
[29]唐旭东,庞永杰,李晔.基于S模型的水下机器人改进人工免疫控制器[J].大连海事大学学报,2008.34(1):50～53
[30]庞永杰,唐旭东.改进人工免疫算法在水下机器人运动控制中的应用研究[J].计算机应用研究,2008.25(9):2640～2642
[31]刘国联,谭冠政,何燕.基于改进人工免疫算法的PID参数优化研究[J].计算机工程与应用, 2008.44(19):84～86
[32]廖亦凡.机械臂液压驱动系统设计与模糊免疫PID控制策略研究[D]:长沙:湖南师范大学电路与系统,2006
[33]王强,钱敏,陈军,等.改进型免疫算法PID设计及在调速系统中的应用[J].电气传动, 2009.39(2):56～60
[34]冯冬青,张志娟.预估模糊免疫PID在房问温度控制中的应用[J].计算机工程与设计,2009. 30(19):4479～4482.
[35]陈少白,谭光兴,毛宗源.基于一种人工免疫算法的PID参数优化[J].武汉科技大学学报, 2006.29(3):313～315
[36]左兴权,李士勇.一种基于人工免疫原理的最优模糊神经网络控制器[J].信息与控制,2004. 33(3):380～385
[37]夏长亮,刘丹,王迎发.无刷直流电机免疫反馈自适应学习人工神经网络控制[J].天津大学学报,2007.40(10):1235～1240
[38] Lee D W .Sim K B.Artificial Immune Network—based Cooperative Control in Collective Autonomous Robots[C] . In : Proc 6th IEEE Int Workshop on Robot and Human Communication Sendai.1997.58～63
[39] Kumak K K.Neidhoefer J.Immunized Neurocontro1[J]. Expert Systems with Applications, l997.13(3):2Ol～214
[40]黄亚玲,贾红红.汽车转向技术发展综述[J].民营科技,2009.6:1,120
[41]臧怀泉,刘敏.EPS参数的优化设计及仿真[J].辽宁工程技术大学学报,2008.27(1):76～78
[42] W.Keith Adams, Richard W.Topping.The Steering Characterizing Functions (SCFs) and Their Use in Steering System Specification,Simulation, and Synthesis.
[43] M.Kamel Salaani. Modeling and Implementation of Steering System Feedback for the National Advanced Driving Simulator.SAE.2002
[44]许洪国.汽车理论[M].北京:人民交通出版社,2008
[45]郭孔辉.轮胎侧偏特性的一般理论模型[J].汽车工程,1990.3:1～12
[46]李伟,刘晓.汽车电动助力转向系统特性研究[J].客车技术与研究,2005.4:1～5
[47]李强.基于分岔理论的电动助力转向系统控制策略及其对汽车操纵稳定性影响的研究[D]:江苏:江苏大学车辆工程系,2007
[48]段广仁.线性系统理论[M].哈尔滨:哈尔滨工业大学出版社,2002
[49]唐子雷.汽车电动助力转向电子控制系统的研究[J].机械管理开发,2007.4:10～12
[50]雷明森,向铁明.汽车电动助力转向的控制策略[J].公路与汽运,2008.7(4):20～22
[51]张春花,李翔晟,肖朝明.电动助力转向系统控制策略研究[J].自动化技术与应,2007.26 (2):30～32
[52]曾群.纯电动汽车电动助力转向系统机理研究与设计[D]:南昌:南昌大学机械电子工程, 2009
[53]黄李琴,季学武,陈奎元.汽车电动助力转向控制系统的初步研究[J].汽车技术,2003.6:3～6
[54]刘慧忱.汽车电动助力转向系统控制规律的研究[D]:重庆:重庆交通大学车辆工程系,2007
[55]刘鹏,姚艳.电动助力转向系统的PID控制及仿真研究[J].机械与电子,2008.(3):41～44
[56]卢娟.电动助力转向系统建模与仿真研究[D]:重庆:重庆大学车辆工程,2006
[57]周冬林,黄菊花,曾群.基于电动助力转向系统控制算法的研究[J].计算技术与自动化,2009.28(1):80～83
[58]刘俊,陈无畏.车辆电动转向系统的卡尔曼滤波模糊PID控制[J].农业机械学报,2007.38 (9):1～5
[59]高明,朱懿韬,许南绍.基于转向盘转动速度变转矩控制的电动助力转向系统[J].重庆工学院学报,2009.23(2):7～12
[60]王柏峰,钟勇,李志强,等.基于径向基神经网络的EPS助力控制方法[J].客车技术与研究,2007.4:12～15
[61]刘照.汽车电动助力转向系统动力学分析与控制方法研究[D]:武汉:华中科技大学机械设计及理论,2004
[62]吴勃夫.基于预测控制的汽车主动悬架与电动助力转向系统集成控制优化设计[D]:合肥:合肥工业大学车辆工程系,2006
[63]王其东,吴勃夫,陈无畏.基于预测控制的主动悬架与电动助力转向集成控制[J].农业机械学报,2007.38(1):1～5
[64]王其东,秦炜华,陈无畏.基于多自由度模型的汽车ASS与EPS集成控制研究[J].系统仿真学报,2009.21(16):5130～5134
[65]蔡自兴.智能控制原理与应用[M].北京:新华大学出版社,2007
[66]李娜,仁庆道尔吉.车间作业调度及其遗传算法[J].内蒙古工业大学学报,2009.1(2):21～26
[67]莫宏伟.人工免疫系统原理与应用[M].哈尔滨:哈尔滨工业大学出版,2003
[68]张乐,陆金桂.改进的免疫算法求解TSP问题[J].计算机工程与应用,2005.87～88.
[69]谭光兴,毛宗源.一种基于模仿者动态模型的免疫算法[J].计算机工程与应用,2006.42 (2):55～57,190
[70]谭光兴,毛宗源,何元烈.一种基于抗体网络的免疫算法[J].计算机工程与设计,2007.28 (5):1104～1107
[71]王康康,唐岚,黎长青.基于AMESim和Simulink的汽车电动助力转向系统的联合仿真,机床与液压[J].2008,6.36(6):107～109
[72] Mechamical Simulation Corporation, Ann Arbor,MI USA.MSC CARSIM User Mannual (version8),2008
[73]冯广刚.基于主被动集成的汽车安全控制系统建模与仿真[D]:湖南:湖南大学车辆工程专业,2008