Abstract
A fully coupled 6-degree-of-freedom nonlinear dynamic model is presented to analyze the dynamic response of a semi-submersible platform which is equipped with the dynamic positioning (DP) system. In the control force design, a dynamic model of reference linear drift frequency in the horizontal plane is introduced. The dynamic surface control (DSC) is used to design a control strategy for the DP. Compared with the traditional back-stepping methods, the dynamic surface control combined with radial basis function (RBF) neural networks (NNs) can avoid differentiating intermediate variables repeatedly in every design step due to the introduction of a first order filter. Low frequency motions obtained from total motions by a low pass filter are chosen to be the inputs for the RBF NNs which are used to approximate the low frequency wave force. Considering the propellers' wear and tear, the effect of filtering frequencies for the control force is discussed. Based on power consumptions and positioning requirements, the NN centers are determined. Moreover, the RBF NNs used to approximate the total wave force are built to monitor the disturbances. With the DP assistance, the results of fully coupled dynamic response simulations are given to illustrate the effectiveness of the proposed control strategy.
| Original language | English |
|---|---|
| Pages (from-to) | 407-414 |
| Number of pages | 8 |
| Journal | Journal of Ocean University of China |
| Volume | 13 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jun 2014 |
| Externally published | Yes |
Keywords
- RBF NNs
- adaptive control
- coupled analysis
- dynamic positioning system
- dynamic surface control
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