J4 ›› 2012, Vol. 9 ›› Issue (4): 508-514.doi: 10.1016/S1672-6529(11)60135-2

• 论文 • 上一篇    

The Model Identification for Small Unmanned Aerial Rotorcraft Based on Adaptive Ant Colony Algorithm

Xusheng Lei1,2, Kexin Guo1   

  1. 1. School of Instrument Science and Opto-electronic Engineering, Beihang University, Beijing 100191, P. R. China
    2. Science and Technology on Inertial Laboratory, Beijing 100191, P. R. China
  • 出版日期:2012-12-30
  • 通讯作者: Xusheng Lei E-mail:xushenglei@buaa.edu.cn

The Model Identification for Small Unmanned Aerial Rotorcraft Based on Adaptive Ant Colony Algorithm

Xusheng Lei1,2, Kexin Guo1   

  1. 1. School of Instrument Science and Opto-electronic Engineering, Beihang University, Beijing 100191, P. R. China
    2. Science and Technology on Inertial Laboratory, Beijing 100191, P. R. China
  • Online:2012-12-30
  • Contact: Xusheng Lei E-mail:xushenglei@buaa.edu.cn

摘要:

This paper proposes a model identification method to get high performance dynamic model of a small unmanned aerial rotorcraft. With the analysis of flight characteristics, a linear dynamic model is constructed by the small perturbation theory. Using the micro guidance navigation and control module, the system can record the control signals of servos, the state information of attitude and velocity information in sequence. After the data preprocessing, an adaptive ant colony algorithm is proposed to get optimal parameters of the dynamic model. With the adaptive adjustment of the pheromone in the selection process, the proposed model identification method can escape from local minima traps and get the optimal solution quickly. Performance analysis and experiments are conducted to validate the effectiveness of the identified dynamic model. Compared with real flight data, the identified model generated by the proposed method has a better performance than the model generated by the adaptive genetic algorithm. Based on the identified dynamic model, the small unmanned aerial rotorcraft can generate suitable control parameters to realize stable hovering, turning, and straight flight.

关键词: small unmanned aerial rotorcraft, model identification, adaptive ant colony

Abstract:

This paper proposes a model identification method to get high performance dynamic model of a small unmanned aerial rotorcraft. With the analysis of flight characteristics, a linear dynamic model is constructed by the small perturbation theory. Using the micro guidance navigation and control module, the system can record the control signals of servos, the state information of attitude and velocity information in sequence. After the data preprocessing, an adaptive ant colony algorithm is proposed to get optimal parameters of the dynamic model. With the adaptive adjustment of the pheromone in the selection process, the proposed model identification method can escape from local minima traps and get the optimal solution quickly. Performance analysis and experiments are conducted to validate the effectiveness of the identified dynamic model. Compared with real flight data, the identified model generated by the proposed method has a better performance than the model generated by the adaptive genetic algorithm. Based on the identified dynamic model, the small unmanned aerial rotorcraft can generate suitable control parameters to realize stable hovering, turning, and straight flight.

Key words: small unmanned aerial rotorcraft, model identification, adaptive ant colony