Anatomy of Discrete Kalman Filter and Its Implementation for Sensorless Velocity Estimation of Organic Actuator
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Anatomy of Discrete Kalman Filter and Its Implementation for Sensorless Velocity Estimation of Organic Actuator. / Schimmack, Manuel; Mercorelli, Paolo.
In: IFAC-PapersOnLine, Vol. 49, No. 6, 2016, p. 110-114.Research output: Journal contributions › Conference article in journal › Research › peer-review
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TY - JOUR
T1 - Anatomy of Discrete Kalman Filter and Its Implementation for Sensorless Velocity Estimation of Organic Actuator
AU - Schimmack, Manuel
AU - Mercorelli, Paolo
N1 - 11th IFAC Symposium on Advances in Control Education ACE 2016 — Bratislava, Slovakia, 1—3 June 2016
PY - 2016
Y1 - 2016
N2 - This paper presents a general derivation of the discrete Kalman filter (DKF) in context of education, with the objective to integrate teaching and research by promoting control and signal processing as a field that embraces science, technology, engineering and mathematics (STEM). In more detail, this contribution showcases a possible lecture structure of the discrete Kalman filter together with an innovative laboratory experiment, suitable for an audience that does not require a strong mathematical background. The importance of finding appropriate didactic methods in the context of KF is due to the intrinsic difficulty which characterises this algorithm to be understood by the students. In general the Kalman filter is one of the most used algorithms in all fields of control systems, thanks to its effectiveness and efficiency. In this contribution the filter is used as a state observer to estimate the velocity of a stimulus-responsive polymerfibre actuator in the proposed laboratory experiment. Besides the theoretical aspects of the discrete Kalman filter algorithm, a step-by-step development for its implementation is presented. The proposed structure is general and can be used as a basic frame for research in the context of control and signal processing. In this sense, this contribution proposes a better understanding of the role of integrating teaching and research in education.
AB - This paper presents a general derivation of the discrete Kalman filter (DKF) in context of education, with the objective to integrate teaching and research by promoting control and signal processing as a field that embraces science, technology, engineering and mathematics (STEM). In more detail, this contribution showcases a possible lecture structure of the discrete Kalman filter together with an innovative laboratory experiment, suitable for an audience that does not require a strong mathematical background. The importance of finding appropriate didactic methods in the context of KF is due to the intrinsic difficulty which characterises this algorithm to be understood by the students. In general the Kalman filter is one of the most used algorithms in all fields of control systems, thanks to its effectiveness and efficiency. In this contribution the filter is used as a state observer to estimate the velocity of a stimulus-responsive polymerfibre actuator in the proposed laboratory experiment. Besides the theoretical aspects of the discrete Kalman filter algorithm, a step-by-step development for its implementation is presented. The proposed structure is general and can be used as a basic frame for research in the context of control and signal processing. In this sense, this contribution proposes a better understanding of the role of integrating teaching and research in education.
KW - Engineering
KW - Education in signal processing and control
KW - discrete Kalman filter
KW - virtual sensor
UR - http://www.scopus.com/inward/record.url?scp=84994851453&partnerID=8YFLogxK
U2 - 10.1016/j.ifacol.2016.07.162
DO - 10.1016/j.ifacol.2016.07.162
M3 - Conference article in journal
VL - 49
SP - 110
EP - 114
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
SN - 2405-8971
IS - 6
ER -