Abstract
System Identification (System ID) plays a key role in control system design and input shaping 1,2. The first thing that a controls engineer learns in the real world is that the transfer function is not written on the outside of the hardware container. So, how does one obtain the transfer function? System ID is used to obtain the transfer function and the critical parameters of simplified systems models that are required for input shaping designs. System models are usually an approximation and need to be refined by comparing to experimental data. On the other hand, empirical models can be developed directly from experimental data when no reasonable theoretical models exist for a system. In any case, System ID provides a systematic way to develop and/or refine the system model. This chapter describes the basic concepts of System ID including linear and nonlinear least squares, as well as, the more advanced concept of homotopy to increase the robustness of the System ID tools. The last section demonstrates the backward propagation technique for multiple-link robots and actuator System ID.
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© 2002 Springer Science+Business Media New York
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Robinett, R.D. et al. (2002). System Identification. In: Flexible Robot Dynamics and Controls. International Federation for Systems Research International Series on Systems Science and Engineering, vol 19. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0539-6_4
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DOI: https://doi.org/10.1007/978-1-4615-0539-6_4
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