| タイトル | Hybrid state-space self-tuning control using dual-rate sampling |
| 著者（英） | Shieh, Leang S.; Zhao, Xiao M.; Sunkel, John W. |
| 著者所属（英） | NASA Johnson Space Center|Houston Univ. |
| 発行日 | 1991-01-01 |
| 言語 | eng |
| 内容記述 | This paper presents a hybrid state-space self-tuning control scheme using dual-rate sampling for suboptimal digital adaptive control of linear time-invariant continuous-time multivariable stochastic systems with unknown parameters. An equivalent fast-rate discrete-time state-space innovation model (with estimated states) of the continuous-time system is constructed by using the estimated system parameters and Kalman gain. To utilize the existing optimal regional-pole assignment method developed in the continuous-time domain, the constructed fast-rate discrete-time model is converted into an equivalent continuous-time model for the development of a state-feedback optimal control law with pole placement in a specific region. The developed analog optimal control law is then converted into an equivalent pseudo-slow-rate digital control law via the proposed digital redesign technique, which can be realized via slow-rate digital electronics. The proposed method enables the development of a digitally implementable advanced control algorithm for digital adaptive control of continuous-time multivariable stochastic systems which may be unstable and/or have nonminimum phase. |
| NASA分類 | CYBERNETICS |
| レポートNO | 91A23624 |
| 権利 | Copyright |
| URI | https://repository.exst.jaxa.jp/dspace/handle/a-is/350329 |
