无人驾驶机器人车辆非线性模糊滑模车速控制
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摘要
为了实现不同行驶工况下车速的精确、稳定控制,提出一种基于非线性干扰观测器的无人驾驶机器人车辆模糊滑模车速控制方法。考虑模型不确定性和外部干扰对车速控制的影响,建立车辆纵向动力学模型。通过分析无人驾驶机器人油门机械腿、制动机械腿的结构、机械腿操纵自动挡车辆踏板的运动,建立油门机械腿和制动机械腿的运动学模型。在此基础上,分别设计油门/制动切换控制器、油门模糊滑模控制器以及制动模糊滑模控制器,并进行控制系统的稳定性分析。油门/制动切换控制器以目标车速的导数为输入来进行油门与制动之间的切换控制。油门模糊滑模控制器和制动模糊滑模控制器以当前车速以及车速误差为输入,分别以油门机械腿直线电机位移和制动机械腿直线电机位移为输出来实现对油门与制动的控制。模糊滑模控制器中,为了减少控制抖振,滑模控制的反馈增益系数由模糊逻辑进行在线调节。模糊滑模控制器中的非线性干扰观测器用于估计和补偿无人驾驶机器人车辆的模型不确定性与外部干扰。仿真及试验结果对比分析表明:本文方法能够精确地估计和补偿无人驾驶机器人车辆的模型不确定性和外部干扰,避免了油门控制与制动控制之间的频繁切换,并实现了精确稳定的车速控制。
The accurate and stable speed control, in different driving conditions for an unmanned driving robotic vehicle(UDRV) was estimated using the fuzzy sliding mode speed control method with a nonlinear disturbance observer(NDO). The vehicle longitudinal dynamics model was established by determining modeling uncertainties and external disturbances. The throttle mechanical leg kinematics model and the brake mechanical leg kinematics model of an unmanned driving robot(UDR) was established by analyzing the structure and movement of the throttle mechanical leg and the brake mechanical leg; the mechanical legs are used to manipulate the pedals of a vehicle with automatic transmission. The throttle/brake switching controller, throttle fuzzy sliding mode controller, and brake fuzzy sliding mode controller were designed, and the stability of the control system was proved based on this analysis. The throttle/brake switching controller was designed to achieve switching of control between the throttle and the brake by taking the derivative of vehicle target speed as the input. The throttle fuzzy sliding mode controller and the brake fuzzy sliding mode controller was designed to achieve control of the throttle and brake by recording actual vehicle speed and speed error as the input and the linear motor displacement of both the throttle mechanical leg and the brake mechanical leg as the output, respectively. Furthermore, to reduce control chattering, the sliding mode feedback control gain of the fuzzy sliding mode controller was adjusted online using the fuzzy logic algorithm. The NDO of the fuzzy sliding mode controller was designed to estimate and compensate for modeling uncertainties and external disturbances of the UDRV. The comparison results between the simulation and experiment demonstrate that the proposed method accurately estimates and compensates for the modeling uncertainties and external disturbances in the UDRV. In addition, frequent switching of control between the throttle and the brake is eliminated, and accurate and stable speed control is achieved.
The accurate and stable speed control, in different driving conditions for an unmanned driving robotic vehicle(UDRV) was estimated using the fuzzy sliding mode speed control method with a nonlinear disturbance observer(NDO). The vehicle longitudinal dynamics model was established by determining modeling uncertainties and external disturbances. The throttle mechanical leg kinematics model and the brake mechanical leg kinematics model of an unmanned driving robot(UDR) was established by analyzing the structure and movement of the throttle mechanical leg and the brake mechanical leg; the mechanical legs are used to manipulate the pedals of a vehicle with automatic transmission. The throttle/brake switching controller, throttle fuzzy sliding mode controller, and brake fuzzy sliding mode controller were designed, and the stability of the control system was proved based on this analysis. The throttle/brake switching controller was designed to achieve switching of control between the throttle and the brake by taking the derivative of vehicle target speed as the input. The throttle fuzzy sliding mode controller and the brake fuzzy sliding mode controller was designed to achieve control of the throttle and brake by recording actual vehicle speed and speed error as the input and the linear motor displacement of both the throttle mechanical leg and the brake mechanical leg as the output, respectively. Furthermore, to reduce control chattering, the sliding mode feedback control gain of the fuzzy sliding mode controller was adjusted online using the fuzzy logic algorithm. The NDO of the fuzzy sliding mode controller was designed to estimate and compensate for modeling uncertainties and external disturbances of the UDRV. The comparison results between the simulation and experiment demonstrate that the proposed method accurately estimates and compensates for the modeling uncertainties and external disturbances in the UDRV. In addition, frequent switching of control between the throttle and the brake is eliminated, and accurate and stable speed control is achieved.
引文
[1] WONG N,CHAMBERS C,STOL K,et al.Development of a Robotic Driver for Autonomous Vehicle Following [J].International Journal of Intelligent Systems Technologies and Applications,2010,8 (1-4):276-287.
[2] 高韬,刘正光,岳士宏,等.用于智能交通的运动车辆跟踪算法[J].中国公路学报,2010,23(3):89-94.GAO Tao,ZHANG Zheng-guang,YUE Shi-hong,et al.Moving Vehicle Tracking Algorithm Used for Intelligent Traffic [J].China Journal of Highway and Transport,2010,23 (3):89-94.
[3] 邱小平,马丽娜,周小霞,等.基于安全距离的手动-自动驾驶混合交通流研究[J].交通运输系统工程与信息,2016,16(4):101-108.QIU Xiao-ping,MA Li-na,ZHOU Xiao-xia,et al.The Mixed Traffic Flow of Manual-automated Driving Based on Safety Distance [J].Journal of Transportation Systems Engineering and Information Technology,2016,16 (4):101-108.
[4] CHEN G,ZHANG W.Hierarchical Coordinated Control Method for Unmanned Robot Applied to Automotive Test [J].IEEE Transactions on Industrial Electronics,2016,63 (2):1039-1051.
[5] HIRATA N,MIZUTANI N,MATSUI H,et al.Fuel Consumption in a Driving Test Cycle by Robotic Driver Considering System Dynamics [C] // IEEE.International Conference on Robotics and Automation.New York:IEEE,2015:3374-3379.
[6] ALT B,HERMANN E,SVARICEK F.Second Order Sliding Modes Control for Rope Winch Based Automotive Driver Robot [J].International Journal of Vehicle Design,2013,62:147-164.
[7] 陈刚,张为公.基于模糊自适应PID的汽车驾驶机器人的车速控制[J].汽车工程,2012,34(6):511-516.CHEN Gang,ZHANG Wei-gong.Speed Control of Vehicle Robot Driver Based on Adaptive Fuzzy PID Control [J].Automotive Engineering,2012,34 (6):511-516.
[8] 王纪伟,陈刚,汪俊.基于模糊免疫PID的驾驶机器人车辆路径及速度跟踪控制[J].南京理工大学学报,2017,41(6):686-692.WANG Ji-wei,CHEN Gang,WANG Jun.Vehicle Path and Speed Tracking Control of Robot Driver Based on Fuzzy Immune PID [J].Journal of Nanjing University of Science and Technology,2017,41 (6):686-692.
[9] CHEN G,ZHANG W,ZHANG X.Speed Tracking Control of Vehicle Robot Driver System Using Multiple Sliding Surface Control Schemes [J].International Journal of Advanced Robotic Systems,2013,10 (2):1-9.
[10] SAILER S,BUCHHOLZ M,DIETMAYER K.Flatness Based Velocity Tracking Control of a Vehicle on a Roller Dynamometer Using a Robotic Driver [C] // IEEE.50th IEEE Conference of Decision and Control.New York:IEEE,2011:7962-7967.
[11] XIA C,WANG W,CHEN G,et al.Robust Control for the Relay ICPT System Under External Disturbance and Parametric Uncertainty [J].IEEE Transactions on Control Systems Technology,2016,25 (6):2168-2175.
[12] NIKDEL N,BADAMCHIZADEH M,AZIMIRAD V,et al.Fractional-order Adaptive Backstepping Control of Robotic Manipulators in the Presence of Model Uncertainties and External Disturbances [J].IEEE Transactions on Industrial Electronics,2016,63 (10):6249-6256.
[13] PRIETO P,CAZAREZ-CASTRO N,AGUILAR L,et al.Chattering Existence and Attenuation in Fuzzy-based Sliding Mode Control [J].Engineering Applications of Artificial Intelligence,2017,61:152-160.
[14] 邹权,钱林方,蒋清山.永磁同步电机伺服系统的自适应模糊滑模控制[J].控制理论与应用,2015,32(6):817-822.ZOU Quan,QIAN Lin-fang,JIANG Qing-shan.Adaptive Fuzzy Sliding-mode Control for Permanent Magnet Synchronous Motor Servo System [J].Control Theory and Applications,2015,32 (6):817-822.
[15] 郭景华,李琳辉,胡平,等.基于模糊逻辑的无人驾驶车纵向多滑模控制[J].中国公路学报,2013,26(1):170-176.GUO Jing-hua,LI Lin-hui,HU Ping,et al.Longitudinal Multiple Sliding-mode Control of Unmanned Vehicle Via Fuzzy Logic [J].China Journal of Highway and Transport,2013,26 (1):170-176.
[16] YAN Y,YANG J,SUN Z,et al.Robust Speed Regulation for PMSM Servo System with Multiple Sources of Disturbances Via an Augmented Disturbance Observer [J].IEEE/ASME Transactions on Mechatronics,2018,23 (2):769-780.
[17] 陈自力,张昊,蔚建斌,等.基于非线性干扰观测器的翼伞鲁棒反步跟踪控制[J].控制与决策,2017,32(8):1427-1433.CHEN Zi-li,ZHANG Hao,WEI Jian-bin,et al.Robust Backstepping Tracking Control Based on Nonlinear Disturbance Observer for Unmanned Parafoil Vehicle [J].Control and Decision,2017,32 (8):1427-1433.
[18] 于靖,陈谋,姜长生.基于干扰观测器的非线性不确定系统自适应滑模控制[J].控制理论与应用,2014,31(8):993-999.YU Jing,CHEN Mou,JIANG Chang-sheng.Adaptive Sliding Mode Control for Nonlinear Uncertain Systems Based on Disturbance Observer [J].Control Theory and Applications,2014,31 (8):993-999.
[19] GB 18352.3—2005,轻型汽车污染物排放限值及测量方法(中国Ⅲ、Ⅳ阶段)[S].GB 18352.3—2005,Limits and Measurement Methods for Emissions from Light-duty Vehicle (Ⅲ,Ⅳ) [S].
[20] 詹兴泉.车用催化转化器评价技术及耐久试验方法间相关性研究[D].武汉:武汉理工大学,2002.ZHAN Xing-quan.Research on Evaluation Technology and Correlation Between Test Methods of Durability of Catalytic Converter for Motor Vehicle [D].Wuhan:Wuhan University of Technology,2002.
[2] 高韬,刘正光,岳士宏,等.用于智能交通的运动车辆跟踪算法[J].中国公路学报,2010,23(3):89-94.GAO Tao,ZHANG Zheng-guang,YUE Shi-hong,et al.Moving Vehicle Tracking Algorithm Used for Intelligent Traffic [J].China Journal of Highway and Transport,2010,23 (3):89-94.
[3] 邱小平,马丽娜,周小霞,等.基于安全距离的手动-自动驾驶混合交通流研究[J].交通运输系统工程与信息,2016,16(4):101-108.QIU Xiao-ping,MA Li-na,ZHOU Xiao-xia,et al.The Mixed Traffic Flow of Manual-automated Driving Based on Safety Distance [J].Journal of Transportation Systems Engineering and Information Technology,2016,16 (4):101-108.
[4] CHEN G,ZHANG W.Hierarchical Coordinated Control Method for Unmanned Robot Applied to Automotive Test [J].IEEE Transactions on Industrial Electronics,2016,63 (2):1039-1051.
[5] HIRATA N,MIZUTANI N,MATSUI H,et al.Fuel Consumption in a Driving Test Cycle by Robotic Driver Considering System Dynamics [C] // IEEE.International Conference on Robotics and Automation.New York:IEEE,2015:3374-3379.
[6] ALT B,HERMANN E,SVARICEK F.Second Order Sliding Modes Control for Rope Winch Based Automotive Driver Robot [J].International Journal of Vehicle Design,2013,62:147-164.
[7] 陈刚,张为公.基于模糊自适应PID的汽车驾驶机器人的车速控制[J].汽车工程,2012,34(6):511-516.CHEN Gang,ZHANG Wei-gong.Speed Control of Vehicle Robot Driver Based on Adaptive Fuzzy PID Control [J].Automotive Engineering,2012,34 (6):511-516.
[8] 王纪伟,陈刚,汪俊.基于模糊免疫PID的驾驶机器人车辆路径及速度跟踪控制[J].南京理工大学学报,2017,41(6):686-692.WANG Ji-wei,CHEN Gang,WANG Jun.Vehicle Path and Speed Tracking Control of Robot Driver Based on Fuzzy Immune PID [J].Journal of Nanjing University of Science and Technology,2017,41 (6):686-692.
[9] CHEN G,ZHANG W,ZHANG X.Speed Tracking Control of Vehicle Robot Driver System Using Multiple Sliding Surface Control Schemes [J].International Journal of Advanced Robotic Systems,2013,10 (2):1-9.
[10] SAILER S,BUCHHOLZ M,DIETMAYER K.Flatness Based Velocity Tracking Control of a Vehicle on a Roller Dynamometer Using a Robotic Driver [C] // IEEE.50th IEEE Conference of Decision and Control.New York:IEEE,2011:7962-7967.
[11] XIA C,WANG W,CHEN G,et al.Robust Control for the Relay ICPT System Under External Disturbance and Parametric Uncertainty [J].IEEE Transactions on Control Systems Technology,2016,25 (6):2168-2175.
[12] NIKDEL N,BADAMCHIZADEH M,AZIMIRAD V,et al.Fractional-order Adaptive Backstepping Control of Robotic Manipulators in the Presence of Model Uncertainties and External Disturbances [J].IEEE Transactions on Industrial Electronics,2016,63 (10):6249-6256.
[13] PRIETO P,CAZAREZ-CASTRO N,AGUILAR L,et al.Chattering Existence and Attenuation in Fuzzy-based Sliding Mode Control [J].Engineering Applications of Artificial Intelligence,2017,61:152-160.
[14] 邹权,钱林方,蒋清山.永磁同步电机伺服系统的自适应模糊滑模控制[J].控制理论与应用,2015,32(6):817-822.ZOU Quan,QIAN Lin-fang,JIANG Qing-shan.Adaptive Fuzzy Sliding-mode Control for Permanent Magnet Synchronous Motor Servo System [J].Control Theory and Applications,2015,32 (6):817-822.
[15] 郭景华,李琳辉,胡平,等.基于模糊逻辑的无人驾驶车纵向多滑模控制[J].中国公路学报,2013,26(1):170-176.GUO Jing-hua,LI Lin-hui,HU Ping,et al.Longitudinal Multiple Sliding-mode Control of Unmanned Vehicle Via Fuzzy Logic [J].China Journal of Highway and Transport,2013,26 (1):170-176.
[16] YAN Y,YANG J,SUN Z,et al.Robust Speed Regulation for PMSM Servo System with Multiple Sources of Disturbances Via an Augmented Disturbance Observer [J].IEEE/ASME Transactions on Mechatronics,2018,23 (2):769-780.
[17] 陈自力,张昊,蔚建斌,等.基于非线性干扰观测器的翼伞鲁棒反步跟踪控制[J].控制与决策,2017,32(8):1427-1433.CHEN Zi-li,ZHANG Hao,WEI Jian-bin,et al.Robust Backstepping Tracking Control Based on Nonlinear Disturbance Observer for Unmanned Parafoil Vehicle [J].Control and Decision,2017,32 (8):1427-1433.
[18] 于靖,陈谋,姜长生.基于干扰观测器的非线性不确定系统自适应滑模控制[J].控制理论与应用,2014,31(8):993-999.YU Jing,CHEN Mou,JIANG Chang-sheng.Adaptive Sliding Mode Control for Nonlinear Uncertain Systems Based on Disturbance Observer [J].Control Theory and Applications,2014,31 (8):993-999.
[19] GB 18352.3—2005,轻型汽车污染物排放限值及测量方法(中国Ⅲ、Ⅳ阶段)[S].GB 18352.3—2005,Limits and Measurement Methods for Emissions from Light-duty Vehicle (Ⅲ,Ⅳ) [S].
[20] 詹兴泉.车用催化转化器评价技术及耐久试验方法间相关性研究[D].武汉:武汉理工大学,2002.ZHAN Xing-quan.Research on Evaluation Technology and Correlation Between Test Methods of Durability of Catalytic Converter for Motor Vehicle [D].Wuhan:Wuhan University of Technology,2002.
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