Asymptotic Properties of Bias Compensated State Space Model Identification Method

2011 ◽  
Vol 44 (1) ◽  
pp. 6505-6510
Author(s):  
Kenji Ikeda ◽  
Hiroshi Oku
2006 ◽  
Vol 51 (2) ◽  
pp. 202-210 ◽  
Author(s):  
Rendy P. Cheng ◽  
Mark B. Tischler ◽  
Greg J. Schulein

2014 ◽  
Vol 598 ◽  
pp. 442-452
Author(s):  
Yu Zhu Liu ◽  
Fei Hu

In order to control an unmanned helicopter accurately and reliably, it is necessary to have a precise mathematical model of its dynamics. This paper presents a new timedomain identification method and process for full state space model of small-scale unmanned helicopters. The identification method is called ISAcwPEM (Improved Simulated Annealing combined with Prediction Error Method), which is not sensitive to initial point selection and doesn’t require frequency-sweeping inputs. Firstly, the primary parameters to be identified are selected by model sensitivity analysis. After that, the improved simulated annealing algorithm runs in a distributed computing platform to figure out a 13-order state space model of the SJTU T-REX700E small-scale unmanned helicopter (consisting of a cruise modal and a hover modal). Then the iterative Prediction Error Method (PEM) is used to optimize the model. In addition, the time-delay term and the trim term are estimated and added to the model. Finally, the effectiveness of the identification method is well validated by real outdoor flight experimental results.


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