Please use this identifier to cite or link to this item:
https://doi.org/10.1109/87.701354
Title: | High-order iterative learning identification of projectile's aerodynamic drag coefficient curve from radar measured velocity data | Authors: | Chen, Y. Wen, C. Xu, J.-X. Sun, M. |
Keywords: | Aerodynamic drag coefficient Curve identification Data reduction Iterative learning control Minimax tracking Optimal tracking control |
Issue Date: | 1998 | Citation: | Chen, Y., Wen, C., Xu, J.-X., Sun, M. (1998). High-order iterative learning identification of projectile's aerodynamic drag coefficient curve from radar measured velocity data. IEEE Transactions on Control Systems Technology 6 (4) : 563-570. ScholarBank@NUS Repository. https://doi.org/10.1109/87.701354 | Abstract: | Extracting projectile's optimal fitting drag coefficient curve Cdf from radar measured velocity data is considered as an optimal tracking control problem (OTCP) where Cdf is regarded as a virtual control function while the radar measured velocity data are taken as the desired output trajectory to be optimally tracked. With a three-degree of freedom (DOF) point mass trajectory prediction model, a high-order iterative learning identification scheme with time varying learning gains is proposed to solve this OTCP with a minimax performance index and an arbitrarily chosen initial control function. The convergence of the high-order iterative learning identification is analyzed and a guideline to choose the time varying learning gains is given. The curve identification results from a set of actual flight testing data are compared and discussed for different learning gains. These results demonstrate that the high-order iterative learning identification is effective and applicable to practical curve identification problems. © 1998 IEEE. | Source Title: | IEEE Transactions on Control Systems Technology | URI: | http://scholarbank.nus.edu.sg/handle/10635/80538 | ISSN: | 10636536 | DOI: | 10.1109/87.701354 |
Appears in Collections: | Staff Publications |
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