Optimization and control application of sensor placement in aeroservoelastic of UAV

In order to suppress aeroservoelastic in high-aspect-ratio flexible UAV, in the present work an advanced sensor placement criterion is developed using Cuckoo search algorithm in combination with an enhanced active control method. The advanced sensor placement criterion basically combines the vibration energy based observability measurement as well as further information on evaluating sensor influence in terms of H₂ norm to balance the low and high frequency modes. By eliminating several nests with worst fitness values in each generation and using self-adaptive feedback scaling factor, the proposed elimination mechanism Cuckoo search (EMCS) algorithm is almost three times faster than the standard one. Subsequently, an enhanced active disturbance rejection control (ADRC) method is proposed for the first time in the active vibration control and wind load alleviation of flexible UAV. It is demonstrated that the enhanced ADRC/PID approach with obtained sensor locations can result in a 45.83% reduction in generalized vibrations energy and about 52.16% reduction in wind load alleviation when compared with designs where the sensor locations are not optimum. Finally, the simulation results show that the optimization algorithm can effectively find the optimal location of sensors. Meanwhile, the suppression of aeroservoelastic can be realized with the utilization of the active control.