Abstract
An unmanned helicopter dynamic model identification method based on immune particle swarm optimization (PSO) algorithm is approved in this paper. In order to improve the search efficiency of PSO and avoid the premature convergence, the PSO algorithm is combined with the immune algorithm. The unmanned helicopter model parameters are coded as particle, the error of flight test and math simulation model is objective function, and the dynamic model of unmanned helicopter is identified. The simulation result shows that the method has high identification precision and can realistically reflect the dynamic characteristics.
| Original language | English |
|---|---|
| Pages (from-to) | 3890-3893 |
| Number of pages | 4 |
| Journal | Applied Mechanics and Materials |
| Volume | 347-350 |
| DOIs | |
| State | Published - 2013 |
| Event | 2013 International Conference on Precision Mechanical Instruments and Measurement Technology, ICPMIMT 2013 - Shenyang, Liaoning, China Duration: 25 May 2013 → 26 May 2013 |
Keywords
- Immune PSO
- Model identification
- Unmanned helicopter