基于自适应RBFNN噪声估计的自抗扰控制在姿态控制中的应用
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摘要
针对旋翼飞行多关节机械臂内部参数不确定性、外部环境和自身机械臂规划运动对飞行平台的干扰问题设计了一种姿态控制方法.首先将跟踪微分器作为期望姿态角的过渡过程,利用自适应RBFNN(径向基函数神经网络)算法对旋翼飞行多关节机械臂内、外部干扰进行逼近估计并实时补偿.然后采用非线性状态误差反馈控制来实现旋翼飞行多关节机械臂的姿态跟踪控制,并利用李亚普诺夫函数进行稳定性分析.最后,在仿真平台上实现该算法,将其仿真结果分别与PID(比例-积分-微分)控制、传统自抗扰控制(ARDC)进行比较分析.并且在实际旋翼飞行多关节机械臂系统上进行了实验,在0.4 s之内三轴姿态角可从0快速跟踪到0.6 rad且无超调.该算法对各通道的扰动有较强的抗干扰性,对系统参数有较强的鲁棒性,并且明显优于ARDC和PID算法.结果说明该算法能有效地解决系统不确定性干扰问题以实现姿态角的准确、快速跟踪.
An attitude control method is designed for the rotor-flying platform to reject disturbances from the uncertainty of the intrinsic parameters of RF-MJM(rotor-flying multi-joint manipulator), the external environment, and the force that the manipulator reacts on the platform during the motion planning. Firstly, the internal and external disturbances of RF-MJM are asymptotically estimated by adaptive RBFNN(radial basis function neural network) algorithm and compensated in real time, setting the tracking differentiator(TD) as transient process of the desired attitude. Then, attitude tracking control of RFMJM is accomplished by using nonlinear state error feedback(NLSEF) control, and the stability is analyzed by Lyapunov function. Finally, the algorithm is implemented on the simulation platform and its result is analyzed through comparing with PID(proportional-integral-differential) control and traditional ADRC(active disturbance rejection control). And the algorithm is testified in the realistic system of RF-MJM, where the three-axis attitude angles can be rapidly tracked from 0 to 0.6 rad in 0.4 s without overshoot. The proposed algorithm significantly outperforms ADRC and PID algorithms, for it is of strong anti-jamming capacity against disturbances from different channels, and of better robustness to system parameters.Results show that the proposed algorithm can effectively resolve the problem of uncertain disturbances in system, and track the attitude rapidly and accurately.
An attitude control method is designed for the rotor-flying platform to reject disturbances from the uncertainty of the intrinsic parameters of RF-MJM(rotor-flying multi-joint manipulator), the external environment, and the force that the manipulator reacts on the platform during the motion planning. Firstly, the internal and external disturbances of RF-MJM are asymptotically estimated by adaptive RBFNN(radial basis function neural network) algorithm and compensated in real time, setting the tracking differentiator(TD) as transient process of the desired attitude. Then, attitude tracking control of RFMJM is accomplished by using nonlinear state error feedback(NLSEF) control, and the stability is analyzed by Lyapunov function. Finally, the algorithm is implemented on the simulation platform and its result is analyzed through comparing with PID(proportional-integral-differential) control and traditional ADRC(active disturbance rejection control). And the algorithm is testified in the realistic system of RF-MJM, where the three-axis attitude angles can be rapidly tracked from 0 to 0.6 rad in 0.4 s without overshoot. The proposed algorithm significantly outperforms ADRC and PID algorithms, for it is of strong anti-jamming capacity against disturbances from different channels, and of better robustness to system parameters.Results show that the proposed algorithm can effectively resolve the problem of uncertain disturbances in system, and track the attitude rapidly and accurately.
引文
[1]谭建豪,王耀南,王媛媛,等.旋翼飞行机器人研究进展[J].控制理论与应用,2015,32(10):1278-1286.Tan J H,Wang Y N,Wang Y Y,et al.The research progress of the rotary-wing flight robot[J].Control Theory&Applications,2015,32(10):1278-1286.
[2]钟杭,王耀南,李玲,等.旋翼飞行机械臂建模及动态重心补偿控制[J].控制理论与应用,2016,33(3):311-319.Zhong H,Wang Y N,Li L,et al.Rotor-flying manipulator modeling and control with dynamic compensation for gravity offset[J].Control Theory&Applications,2016,33(3):311-319.
[3]Xu G H,Mo Z.Modified adaptive flight control of quadrotor based on single neuron PID[C]//International Conference on Information Science and Technology.Piscataway,USA:IEEE,2013:313-316.
[4]李杰,齐晓慧,韩帅涛.基于GA-Vague-PID的小型四旋翼飞行器姿态控制方法[J].自动化技术与应用,2013,32(3):1-6.Li J,Qi X H,Han S T.Attitude control for the small quadrotor aircraft based on GA-Vague-PID[J].Techniques of Automation and Applications,2013,32(3):1-6.
[5]王亮,刘向东,盛永智.基于高阶滑模观测器的自适应时变滑模再入姿态控制[J].控制与决策,2014,29(2):281-286.Wang L,Liu X D,Sheng Y Z.High-order sliding mode observer based adaptive time-varying sliding mode for re-entry attitude control[J].Control and Decision,2014,29(2):281-286.
[6]Li S S,Wang Y N,Tan J H,et al.Adaptive RBFNNs/integral sliding mode control for a quadrotor aircraft[J].Neurocomputing,2016,216(C):126-134.
[7]甄红涛,齐晓慧,李杰,等.四旋翼无人机L1自适应块控反步姿态控制器设计[J].控制与决策,2014,29(6):1076-1082.Zhen H T,Qi X H,Li J,et al.Quadrotor UAV L1 adaptive block backstepping attitude controller[J].Control and Decision,2014,29(6):1076-1082.
[8]腾雄.微小型四旋翼飞行器轨迹跟踪研究与应用[D].武汉:武汉科技大学,2016.Teng X.Research and application on trajectory tracking for micro air vehicle quadrotor[D].Wuhan:Wuhan University of Science and Technology,2016.
[9]陈骥.四旋翼无人飞行器动力学建模及控制技术的研究[D].南京:南京理工大学,2016.Chen J.The research of rotorcraft on dynamic modeling and control technology[D].Nanjing:Nanjing University of Science&Technology,2016.
[10]腾雄,吴怀宇,陈洋,等.基于反步法的四旋翼飞行器轨迹跟踪研究[J].计算机仿真,2016,33(5):78-83.Teng X,Wu H Y,Chen Y,et al.Trajectory tracking of quadrotor aircrafts base on backstepping[J].Computer Simulation,2016,33(5):78-83.
[11]王俊生,马宏绪,蔡文澜,等.基于ADRC的小型四旋翼无人直升机控制方法研究[J].弹箭与制导学报,2008,28(3):31-40.Wang J S,Ma H X,Cai W L,et al.Research on micro quadrotor control based on ADRC[J].Journal of Projectiles,Rockets,Missiles and Guidance,2008,28(3):31-40.
[12]韩京清.自抗扰控制技术[M].北京:国防工业出版社,2008.Han J Q.Disturbance rejection control technology[M].Beijing:National Defense Industry Press,2008.
[13]刘金琨.先进PID控制MATLAB仿真[M].北京:电子工业出版社,2016:320-323.Liu J K.Advanced PID control and MATLAB simulation[M]Beijing:Publishing House of Electronics Industry,2016:320-323.
[14]叶政.PID控制器参数整定方法研究及应用[D].北京:北京邮电大学,2016.Ye Z.PID controller parameter tuning method and application[D].Beijing:Beijing University of Posts and Telecommunications,2016.
[15]刘一莎,杨晟萱,王伟.四旋翼飞行器的自抗扰飞行控制方法[J].控制理论与应用,2015,32(10):1351-1360.Liu Y S,Yang C X,Wang W.An active disturbance rejection flight control method for quad-rotor unmanned aerial vehicles[J].Control Theory&Applications,2015,32(10):1351-1360.
[16]牛志玲,潘晓萌.基于双种群遗传算法的四旋翼飞行器PID参数整定方法[J].计算机测量与控制,2014,22(4):1230-1232.Niu Z L,Pan X M.Quadrotor’s PID parameters tuning method based on dual population genetic algorithm[J].Computer Measurement&Control,2014,22(4):1230-1232.
[2]钟杭,王耀南,李玲,等.旋翼飞行机械臂建模及动态重心补偿控制[J].控制理论与应用,2016,33(3):311-319.Zhong H,Wang Y N,Li L,et al.Rotor-flying manipulator modeling and control with dynamic compensation for gravity offset[J].Control Theory&Applications,2016,33(3):311-319.
[3]Xu G H,Mo Z.Modified adaptive flight control of quadrotor based on single neuron PID[C]//International Conference on Information Science and Technology.Piscataway,USA:IEEE,2013:313-316.
[4]李杰,齐晓慧,韩帅涛.基于GA-Vague-PID的小型四旋翼飞行器姿态控制方法[J].自动化技术与应用,2013,32(3):1-6.Li J,Qi X H,Han S T.Attitude control for the small quadrotor aircraft based on GA-Vague-PID[J].Techniques of Automation and Applications,2013,32(3):1-6.
[5]王亮,刘向东,盛永智.基于高阶滑模观测器的自适应时变滑模再入姿态控制[J].控制与决策,2014,29(2):281-286.Wang L,Liu X D,Sheng Y Z.High-order sliding mode observer based adaptive time-varying sliding mode for re-entry attitude control[J].Control and Decision,2014,29(2):281-286.
[6]Li S S,Wang Y N,Tan J H,et al.Adaptive RBFNNs/integral sliding mode control for a quadrotor aircraft[J].Neurocomputing,2016,216(C):126-134.
[7]甄红涛,齐晓慧,李杰,等.四旋翼无人机L1自适应块控反步姿态控制器设计[J].控制与决策,2014,29(6):1076-1082.Zhen H T,Qi X H,Li J,et al.Quadrotor UAV L1 adaptive block backstepping attitude controller[J].Control and Decision,2014,29(6):1076-1082.
[8]腾雄.微小型四旋翼飞行器轨迹跟踪研究与应用[D].武汉:武汉科技大学,2016.Teng X.Research and application on trajectory tracking for micro air vehicle quadrotor[D].Wuhan:Wuhan University of Science and Technology,2016.
[9]陈骥.四旋翼无人飞行器动力学建模及控制技术的研究[D].南京:南京理工大学,2016.Chen J.The research of rotorcraft on dynamic modeling and control technology[D].Nanjing:Nanjing University of Science&Technology,2016.
[10]腾雄,吴怀宇,陈洋,等.基于反步法的四旋翼飞行器轨迹跟踪研究[J].计算机仿真,2016,33(5):78-83.Teng X,Wu H Y,Chen Y,et al.Trajectory tracking of quadrotor aircrafts base on backstepping[J].Computer Simulation,2016,33(5):78-83.
[11]王俊生,马宏绪,蔡文澜,等.基于ADRC的小型四旋翼无人直升机控制方法研究[J].弹箭与制导学报,2008,28(3):31-40.Wang J S,Ma H X,Cai W L,et al.Research on micro quadrotor control based on ADRC[J].Journal of Projectiles,Rockets,Missiles and Guidance,2008,28(3):31-40.
[12]韩京清.自抗扰控制技术[M].北京:国防工业出版社,2008.Han J Q.Disturbance rejection control technology[M].Beijing:National Defense Industry Press,2008.
[13]刘金琨.先进PID控制MATLAB仿真[M].北京:电子工业出版社,2016:320-323.Liu J K.Advanced PID control and MATLAB simulation[M]Beijing:Publishing House of Electronics Industry,2016:320-323.
[14]叶政.PID控制器参数整定方法研究及应用[D].北京:北京邮电大学,2016.Ye Z.PID controller parameter tuning method and application[D].Beijing:Beijing University of Posts and Telecommunications,2016.
[15]刘一莎,杨晟萱,王伟.四旋翼飞行器的自抗扰飞行控制方法[J].控制理论与应用,2015,32(10):1351-1360.Liu Y S,Yang C X,Wang W.An active disturbance rejection flight control method for quad-rotor unmanned aerial vehicles[J].Control Theory&Applications,2015,32(10):1351-1360.
[16]牛志玲,潘晓萌.基于双种群遗传算法的四旋翼飞行器PID参数整定方法[J].计算机测量与控制,2014,22(4):1230-1232.Niu Z L,Pan X M.Quadrotor’s PID parameters tuning method based on dual population genetic algorithm[J].Computer Measurement&Control,2014,22(4):1230-1232.