Application of the state‐dependent Riccati equation for flexible‐joint arms: Controller and estimator design

Application of the state‐dependent Riccati equation for flexible‐joint arms: Controller and... Full feedback data is mostly essential in control design. Measuring the links' variation of a flexible‐joint robot (FJR) is easy but not for its actuators. The measurement of states and workspace are also affected by noise and disturbance, respectively; hence, a state observer or a nonlinear estimator is very helpful to improve the control performance of a dynamic system. The state‐dependent Riccati equation (SDRE) is one of the most promising methods in the field of nonlinear optimal observers for estimating variables of multiple‐input–multiple‐output systems. Systematic procedure, simple structure, and incorporation of a wide range of systems (under an observability condition) are some of the advantages of the method. Therefore, the aim of this study is to compose the SDRE controller and estimator simultaneously to reduce the state error of the system in the presence of external disturbance and noise. The application of this method is shown for FJRs in the estimation of changes in motion behind the connection of the motor and link where there is no easy way to measure. The proposed composition of the SDRE controller and estimator was implemented on a 6R robot to examine the various aspects of FJR systems. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Optimal Control Applications and Methods Wiley

Application of the state‐dependent Riccati equation for flexible‐joint arms: Controller and estimator design

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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
Copyright © 2018 John Wiley & Sons, Ltd.
ISSN
0143-2087
eISSN
1099-1514
D.O.I.
10.1002/oca.2377
Publisher site
See Article on Publisher Site

Abstract

Full feedback data is mostly essential in control design. Measuring the links' variation of a flexible‐joint robot (FJR) is easy but not for its actuators. The measurement of states and workspace are also affected by noise and disturbance, respectively; hence, a state observer or a nonlinear estimator is very helpful to improve the control performance of a dynamic system. The state‐dependent Riccati equation (SDRE) is one of the most promising methods in the field of nonlinear optimal observers for estimating variables of multiple‐input–multiple‐output systems. Systematic procedure, simple structure, and incorporation of a wide range of systems (under an observability condition) are some of the advantages of the method. Therefore, the aim of this study is to compose the SDRE controller and estimator simultaneously to reduce the state error of the system in the presence of external disturbance and noise. The application of this method is shown for FJRs in the estimation of changes in motion behind the connection of the motor and link where there is no easy way to measure. The proposed composition of the SDRE controller and estimator was implemented on a 6R robot to examine the various aspects of FJR systems.

Journal

Optimal Control Applications and MethodsWiley

Published: Jan 1, 2018

Keywords: ; ; ; ;

References

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