考虑输入饱和的船舶减摇鳍控制设计

发布时间：2019-01-06 10:41

【摘要】：大幅度横摇严重影响船舶航行的安全性、适航性、舒适性以及军舰的战斗力,如何更快更精确地控制船舶横摇成为船舶运动控制领域的重点研究对象。目前大多数船用减摇鳍系统仍然采用PID控制器。由于船舶横摇运动具有严重的非线性、复杂性以及外界干扰的非线性和不确定性,使得经典的PID控制效果难以满足人们的需求。因此,采用更为先进的控制算法是解决该问题的有效途径。不确定性可能会导致系统不稳定或控制性能变差,而提高控制器的鲁棒性是解决该问题的一种有效方法。本文针对不确定非线性船舶减摇鳍控制系统开展了鲁棒智能控制设计研究。首先,针对参数未知的减摇鳍控制系统,讨论了基于Lyapunov稳定性的参数自适应后推算法。该类控制算法对参数依赖程度较大,控制器的鲁棒性还有待提高。其次,针对含有未知方程和输入饱和的减摇鳍控制系统,利用自适应后推技术和神经网络技术,提出了一种直接自适应神经网络算法。该算法不依赖对象模型,显著提高了控制器的鲁棒性。最后,针对含有未知参数、未建模动态、随机海浪和输入饱和的减摇鳍控制系统,提出了一种自适应干扰观测器算法。该算法解决了含有未知参数的系统无法直接构建干扰观测器这一难题,对系统模型依赖程度低,并进一步提高了控制器的鲁棒性。本文探讨的三种减摇鳍算法鲁棒性依次递增,能够保证了闭环系统的稳定性,并在后两种算法中考虑了系统的输入饱和现象,进一步增强了系统的稳定性。最后以MATLAB软件为工具进行仿真研究,验证了算法的有效性。
[Abstract]:The safety, seaworthiness, comfort and combat effectiveness of warships are seriously affected by large roll rolling. How to control ship rolling more quickly and accurately has become an important research object in the field of ship motion control. At present, most ship fin stabilizers still use PID controller. Due to the serious nonlinearity, complexity and nonlinearity and uncertainty of ship rolling motion, the classical PID control effect is difficult to meet the needs of people. Therefore, more advanced control algorithm is an effective way to solve this problem. Uncertainty may lead to instability or poor control performance, and improving the robustness of the controller is an effective method to solve the problem. In this paper, robust intelligent control design for uncertain nonlinear ship fin stabilizer system is studied. Firstly, for the fin stabilizer control system with unknown parameters, a parameter adaptive back-reckoning method based on Lyapunov stability is discussed. This kind of control algorithm has a large degree of dependence on parameters, and the robustness of the controller needs to be improved. Secondly, a direct adaptive neural network algorithm is proposed for fin stabilizer control system with unknown equations and input saturation. The algorithm is independent of the object model and improves the robustness of the controller significantly. Finally, an adaptive disturbance observer algorithm is proposed for the fin stabilizer control system with unknown parameters, unmodeled dynamic, random wave and input saturation. The algorithm solves the problem that the disturbance observer can not be constructed directly by the system with unknown parameters, and it is less dependent on the system model, and further improves the robustness of the controller. The robustness of the three fin stabilizers discussed in this paper increases in turn, which can ensure the stability of the closed-loop system. In the latter two algorithms, the input saturation of the system is considered and the stability of the system is further enhanced. Finally, the effectiveness of the algorithm is verified by using MATLAB software as a simulation tool.
【学位授予单位】：大连海事大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U664.72

【参考文献】