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Time Series Modeling for Analysis and ControlAdvanced Autopilot Systems

Time Series Modeling for Analysis and Control: Advanced Autopilot Systems [In the previous chapter, we presented three types of autopilot system based on the stationary linear AR model. However, actual sea conditions may change gradually or abruptly due to various factors, and in such a situation, we must consider a nonstationary time series. Furthermore, it may become necessary to consider the nonlinear response of the ship, which will be of particular importance to tracking control. In this chapter, we propose extensions of our statistical optimal controller based on the locally stationary AR model and the RBF-ARX model and develop a noise-adaptive autopilot and a path-tracking autopilot.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Time Series Modeling for Analysis and ControlAdvanced Autopilot Systems

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Publisher
Springer Japan
Copyright
© The Author(s) 2015
ISBN
978-4-431-55302-1
Pages
83 –115
DOI
10.1007/978-4-431-55303-8_4
Publisher site
See Chapter on Publisher Site

Abstract

[In the previous chapter, we presented three types of autopilot system based on the stationary linear AR model. However, actual sea conditions may change gradually or abruptly due to various factors, and in such a situation, we must consider a nonstationary time series. Furthermore, it may become necessary to consider the nonlinear response of the ship, which will be of particular importance to tracking control. In this chapter, we propose extensions of our statistical optimal controller based on the locally stationary AR model and the RBF-ARX model and develop a noise-adaptive autopilot and a path-tracking autopilot.]

Published: Mar 20, 2015

Keywords: Noise adaptive autopilot; RBF-ARX model based predictive control; Ship tracking control; GPS signal based ship tracking error measuring; Ship trajectory tracking dynamics modeling

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