Input Design for Systems Under Identification as Applied to Ultrasonic Transducers
An input design system identification (IDSI) method is outlined in this chapter based on input/output data gathered from random excitation of a system so as to excite all modes. The data set is then used to compose a new set of more focused input data, from which the system is excited again and identified. In this chapter, the input design method is used for the system identification of an ultrasonic sensor pair (transmitter–receiver) so as to obtain an accurate model for it. This model is essential for the analysis of a 3D position estimation system that uses ultrasonic transducers. A single transmitter is attached to the point of interest, and its position is triangulated based on signals received at multiple receivers fixed in a 3D environment. An accurate model for the response of the ultrasonic receivers is essential in the eventual optimization of the entire system. This chapter only presents results for a single pair (called the system in this chapter), but the results will be applicable for the entire 3D system. Results are given that show the comparison of the actual output signal of the system and the output of the model obtained from the IDSI method as well as the identifiability indicator and an identified state-space model. It is shown that the IDSI improves system identification even in the presence of excessive noise.
KeywordsUltrasonic Transducer Input Design Single Transmitter System Identification Method Markov Parameter
- 4.Chen CW, Juang J-N, Huang J-K (1993) Adaptive linear identification and state estimation. In: Leondes CT (ed) Control and dynamic systems: advances in theory and applications, vol 57, multidisciplinary engineering systems: design and optimization techniques and their application. Academic, New York, pp 331–368Google Scholar
- 7.Schoen MP (1997) Input design for system under identification. PhD dissertation, Old Dominion UniversityGoogle Scholar
- 9.Schoen MP, Kuo C-H, Chinvorarat S, Huang J-K (1997) Parameter identifiability for system under identification using ARX models. In: Proceedings of the 18th ASEM conference, Virginia Beach, VA, October 23–26, pp 175–181Google Scholar