Predictive Controller with UKBF for Marine Dynamic Positioning System
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摘要: 为了精准设计水面船舶动力定位控制系统，将无迹卡尔曼布西滤波与非切换解析模型预测控制方法相结合提出一种预测控制器的设计方法.采用无迹卡尔曼布西滤波算法解决非线性连续系统的滤波问题，获取船舶运动状态的估计值；结合相对阶概念，根据船舶运动非线性模型，应用非切换解析模型预测控制方法设计动力定位非线性控制器，使船舶保持在指定位置.研究结果表明：设计控制器的输出较为平滑，有利于减少推进器磨损；设计控制器使船舶北向位置调节时间小于40 s，超调量小于5%，东向位置调节时间小于60 s，超调量小于5%，艏向角度的最大偏移量小于1.5°，令船舶快速到达了指定位置.Abstract: For surface vessel dynamic positioning (DP) system controls, a design method for predictive controllers is proposed based on the unscented Kalman-Bucy filtering (UKBF) algorithm and on a non-switching analytical model predictive control (NSAMPC) method. To avoid linearization and discretization errors in the model, the UKBF algorithm was applied to determine motion-state estimates of the ship. On the basis of the relative degree concept and non-linear ship motion models, an NSAMPC controller was designed in order to maintain a floating vessel at a specific position. The proposed method was verified by performing simulations on a marine supply vessel. The simulation results exhibit a smoother output of the designed controller, which is helpful for reducing the wear on the propeller. Moreover, the proposed controller results in a settling time of less than 40 s for the north position of the vessel with an overshoot of less than 5%. Likewise, the controller results in an east-position settling time of less than 60 s with an overshoot of less than 5%. In addition, the maximum offset of the vessel heading angle is less than 1.5°. The proposed controller allows the ship to reach the specific position quickly.
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Key words:
- dynamic positioning /
- UKBF /
- relative degree /
- predictive controller
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