Opto-electronic platform tracking control of multi-rotor unmanned aerial vehicles based on composite disturbance compensation

Airborne opto-electronic platforms are very important in unmanned aerial vehicle systems. The stability and tracking performance of airborne opto-electronic platforms are easily affected by disturbance factors, making compensating for those disturbances a very prominent issue. In this paper, compared to the traditional disturbance observer, an improved velocity signal based disturbance observer (IVDOB) is particularly designed to compensate for the disturbance. Then its capability, robustness, and stability are discussed. For improving the stabilization accuracy and tracking performance of airborne opto-electronic platforms, the universal approximation property of fuzzy systems is used to compensate the disturbance further and an adaptive fuzzy control system based on IVDOBs is proposed. To validate the scheme, a series of experiments were carried out. The results show that the proposed control scheme can achieve reliable control precision and satisfy the requirements of airborne opto-electronic platform tasks.

[1]  尹传历 Yin Chuan-li,et al.  Velocity based disturbance observer and its application to photoelectric stabilized platform , 2011 .

[2]  Wei We Design of the disturbance observer of opto-electronic platform in frequency domain , 2015 .

[3]  魏伟,et al.  Parameter Tuning Rule for Velocity Based Disturbance Observer , 2014 .

[4]  Li Qi Adaptive Fuzzy PID Control for LOS Stabilization System on Gyro Stabilized Platf orm , 2007 .

[5]  Yoichi Hori,et al.  Robust servosystem design with two degrees of freedom and its application to novel motion control of robot manipulators , 1993, IEEE Trans. Ind. Electron..

[6]  J. M. Hilkert,et al.  Gimbal system configurations and line-of-sight control techniques for small UAV applications , 2013, Defense, Security, and Sensing.

[7]  Zhan Ping,et al.  A control scheme based on RBF Neural Network for High-precision Servo System , 2010, 2010 IEEE International Conference on Mechatronics and Automation.

[8]  Xusheng Lei,et al.  An adaptive decoupling control for three-axis gyro stabilized platform based on neural networks , 2015 .

[9]  I.S. Sarwar,et al.  Modeling, analysis and simulation of a Pan Tilt Platform based on linear and nonlinear systems , 2008, 2008 IEEE/ASME International Conference on Mechtronic and Embedded Systems and Applications.

[11]  陈松林,et al.  Disturbance observer-based robust perfect tracking control for flight simulator , 2015 .

[12]  朱明 Zhu Ming,et al.  Actuality of Photoelectricity Platform and Tracking System for UVA , 2011 .

[13]  Bai Yue,et al.  A composite disturbance compensation method for airborne platform based on improved disturbance observer , 2015 .

[14]  Qi Li,et al.  Adaptive fuzzy PID composite control with hysteresis-band switching for line of sight stabilization servo system , 2011 .

[15]  黄猛 Huang Meng,et al.  Application of high order observer in EO stabilized platform , 2015 .

[16]  Tatsuo Narikiyo,et al.  A Construction of Disturbance Observer to Cope with Frequency Variation and Its Application to Vibration Suppression Control System , 2008 .

[17]  Shen Jian-xin A Low Speed Servo Motor Drive System With Disturbance Torque Observers , 2012 .

[18]  Laurent Itti,et al.  Multilayer real-time video image stabilization , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[19]  Ho-Hwan Chun,et al.  On the design of a disturbance observer for moving target tracking of an autonomous surveillance robot , 2012 .

[20]  He Zhong-liang Control method with improved disturbance observer , 2010 .

[21]  Meng Wang,et al.  A novel servo control method based on feedforward control – Fuzzy-grey predictive controller for stabilized and tracking platform system , 2016 .

[22]  H. Eisenbeiss A MINI UNMANNED AERIAL VEHICLE (UAV): SYSTEM OVERVIEW AND IMAGE ACQUISITION , 2004 .

[23]  Xusheng Lei,et al.  A composite control method based on the adaptive RBFNN feedback control and the ESO for two-axis inertially stabilized platforms. , 2015, ISA transactions.

[24]  Shusheng Li,et al.  Estimation and compensation of unknown disturbance in three-axis gyro-stabilized camera mount , 2015 .

[25]  Lei Guo,et al.  Disturbance-Observer-Based Control and Related Methods—An Overview , 2016, IEEE Transactions on Industrial Electronics.

[26]  Nabil Aouf,et al.  Vision Based Autonomous Landing of Multirotor UAV on Moving Platform , 2017, J. Intell. Robotic Syst..

[27]  Rajani K. Mudi,et al.  A robust self-tuning scheme for PI- and PD-type fuzzy controllers , 1999, IEEE Trans. Fuzzy Syst..

[28]  Kyo-Beum Lee,et al.  Disturbance observer that uses radial basis function networks for the low speed control of a servo motor , 2005 .

[29]  Li Xun,et al.  Design of Self Balancing Anti Disturbance System for Multi Rotor UAV , 2016 .

[30]  Carl J. Kempf,et al.  Disturbance observer and feedforward design for a high-speed direct-drive positioning table , 1999, IEEE Trans. Control. Syst. Technol..