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Applied system identification
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In this paper, the authors introduce the concept of Frequency Domain System ID (FDSI) and Frequency Response Functions (FRF) for time-domain models, as well as Frequency-Domain Models with Random Variables and Kalman Filter.Abstract:
1. Introduction. 2. Time-Domain Models. 3. Frequency-Domain Models. 4. Frequency Response Functions. 5. System Realization. 6. Observer Identification. 7. Frequency Domain System ID. 8. Observer/Controller ID. 9. Recursive Techniques. Appendix A: Fundamental Matrix Algebra. Appendix B: Random Variables and Kalman Filter. Appendix C: Data Acquisition.read more
Citations
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Proceedings ArticleDOI
Adaptive control of aircraft lateral motion with an unknown transition to nonmimimum-phase dynamics
TL;DR: This work applies retrospective cost adaptive control (RCAC) to a linearized aircraft dynamics with an unknown transition to nonminimum-phase (NMP) dynamics, and uses system identification techniques to identify the NMP zero and uses this information in RCAC.
Journal ArticleDOI
State-Space Modeling to Simplify Soil Phosphorus Fractionation
Xiufu Shuai,Russell Yost +1 more
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Journal ArticleDOI
Experimental Modelling of Propulsion Transients of a Brushless DC Motor and Propeller Pair under Limited Power Conditions: A Neural Network Based Approach
TL;DR: An experimental framework to describe the dynamic behavior of brushless direct current (BLDC) motors, which are frequently used in unmanned aerial vehicle (UAV) applications, and a Neural Network (NN) based approach is chosen to handle this modeling issue.