Attitude identification method for unmanned helicopter based on fuzzy model at hovering is presented. The dynamical attitude model is considered as basis for attitude control and it is very complex. To reduce the comp...Attitude identification method for unmanned helicopter based on fuzzy model at hovering is presented. The dynamical attitude model is considered as basis for attitude control and it is very complex. To reduce the complexity of model, nonlinear model of unmanned helicopter with unknown parameters are to be determined by fuzzy system first and then derivative based gradient method is used to identify unknown parameters of model. Gradient method is used due to ability that fuzzy system is not necessarily to be linear in parameters, therefore all fuzzy sets for input and output can be adjusted. The validity of the proposed model was verified using experimental data obtained by the commercially available flight simulator X-Plane. The simulation results showed high accuracy of the modeling method and attitude dynamics data matched well with experimental data.展开更多
This paper proposes a novel method for Small Unmanned Helicopter （SUH） system identification based on Improved Particle Swarm Optimization （IPSO）. In the proposed IPSO, every particle will do a local search as a ...This paper proposes a novel method for Small Unmanned Helicopter （SUH） system identification based on Improved Particle Swarm Optimization （IPSO）. In the proposed IPSO, every particle will do a local search as a ＂self-check＂ before up- dating the global velocity and position. Then, the global best particle is created by a certain number of elitist particles in order to get a rapid rate of convergence during calculation. Thus both the diversity and convergence speed can be taken into considera- tion during a search. Formulated by the first principles derivation, a state-space model is built for the analysis of dynamic modes of an experimental SUH. The helicopter is equipped with an Attitude Heading Reference System （AHRS） and the corresponding data storage modules, which are used for flight test data measurement and recording. After data collection and reconstruction, the input and output data are utilized to determine the corresponding aerodynamic parameters of the state-space model. The predictive accuracy and fidelity of the identified model are verified by making a time-domain comparison between the responses from the simulation model and the responses from actual flight experiments. The results show that the characteristics of the experimental SUH can be determined accurately using the identified model and the new method can be used for SUH system identification with high efficiency and reliability.展开更多
Yaw control is signi¯cant to the attitude control of small unmanned helicopters(SUHs).Since the existing robust control method cannot be applied to the SUH with unknown dynamics and disturbances,this paper propos...Yaw control is signi¯cant to the attitude control of small unmanned helicopters(SUHs).Since the existing robust control method cannot be applied to the SUH with unknown dynamics and disturbances,this paper proposes an improved active disturbance rejection control(IADRC)to solve the problem.The IADRC obtains the optimal solution of the actuator gain(b0)by gradient descent.Besides,this paper summarizes some experiences during the tuning process of ADRC,which signi¯cantly reduces the di±culty of designing ADRC.Finally,the experimental results show that the proposed method is better than the traditional PID in robust and tracking control performance.展开更多
文摘Attitude identification method for unmanned helicopter based on fuzzy model at hovering is presented. The dynamical attitude model is considered as basis for attitude control and it is very complex. To reduce the complexity of model, nonlinear model of unmanned helicopter with unknown parameters are to be determined by fuzzy system first and then derivative based gradient method is used to identify unknown parameters of model. Gradient method is used due to ability that fuzzy system is not necessarily to be linear in parameters, therefore all fuzzy sets for input and output can be adjusted. The validity of the proposed model was verified using experimental data obtained by the commercially available flight simulator X-Plane. The simulation results showed high accuracy of the modeling method and attitude dynamics data matched well with experimental data.
基金This research was supported by the Aeronautical Science Foundation of China （Grant No. 20152853029）. The authors are grateful to Yang Li and Pengxiang Li for their invaluable assistance during the outdoor flight experiments.
文摘This paper proposes a novel method for Small Unmanned Helicopter （SUH） system identification based on Improved Particle Swarm Optimization （IPSO）. In the proposed IPSO, every particle will do a local search as a ＂self-check＂ before up- dating the global velocity and position. Then, the global best particle is created by a certain number of elitist particles in order to get a rapid rate of convergence during calculation. Thus both the diversity and convergence speed can be taken into considera- tion during a search. Formulated by the first principles derivation, a state-space model is built for the analysis of dynamic modes of an experimental SUH. The helicopter is equipped with an Attitude Heading Reference System （AHRS） and the corresponding data storage modules, which are used for flight test data measurement and recording. After data collection and reconstruction, the input and output data are utilized to determine the corresponding aerodynamic parameters of the state-space model. The predictive accuracy and fidelity of the identified model are verified by making a time-domain comparison between the responses from the simulation model and the responses from actual flight experiments. The results show that the characteristics of the experimental SUH can be determined accurately using the identified model and the new method can be used for SUH system identification with high efficiency and reliability.
文摘Yaw control is signi¯cant to the attitude control of small unmanned helicopters(SUHs).Since the existing robust control method cannot be applied to the SUH with unknown dynamics and disturbances,this paper proposes an improved active disturbance rejection control(IADRC)to solve the problem.The IADRC obtains the optimal solution of the actuator gain(b0)by gradient descent.Besides,this paper summarizes some experiences during the tuning process of ADRC,which signi¯cantly reduces the di±culty of designing ADRC.Finally,the experimental results show that the proposed method is better than the traditional PID in robust and tracking control performance.
