發(fā)布時間：2019-01-06 10:41

【摘要】：大幅度橫搖嚴(yán)重影響船舶航行的安全性、適航性、舒適性以及軍艦的戰(zhàn)斗力,如何更快更精確地控制船舶橫搖成為船舶運動控制領(lǐng)域的重點研究對象。 目前大多數(shù)船用減搖鰭系統(tǒng)仍然采用PID控制器。由于船舶橫搖運動具有嚴(yán)重的非線性、復(fù)雜性以及外界干擾的非線性和不確定性,使得經(jīng)典的PID控制效果難以滿足人們的需求。因此,采用更為先進(jìn)的控制算法是解決該問題的有效途徑。 不確定性可能會導(dǎo)致系統(tǒng)不穩(wěn)定或控制性能變差,而提高控制器的魯棒性是解決該問題的一種有效方法。本文針對不確定非線性船舶減搖鰭控制系統(tǒng)開展了魯棒智能控制設(shè)計研究。首先,針對參數(shù)未知的減搖鰭控制系統(tǒng),討論了基于Lyapunov穩(wěn)定性的參數(shù)自適應(yīng)后推算法。該類控制算法對參數(shù)依賴程度較大,控制器的魯棒性還有待提高。其次,針對含有未知方程和輸入飽和的減搖鰭控制系統(tǒng),利用自適應(yīng)后推技術(shù)和神經(jīng)網(wǎng)絡(luò)技術(shù),提出了一種直接自適應(yīng)神經(jīng)網(wǎng)絡(luò)算法。該算法不依賴對象模型,顯著提高了控制器的魯棒性。最后,針對含有未知參數(shù)、未建模動態(tài)、隨機(jī)海浪和輸入飽和的減搖鰭控制系統(tǒng),提出了一種自適應(yīng)干擾觀測器算法。該算法解決了含有未知參數(shù)的系統(tǒng)無法直接構(gòu)建干擾觀測器這一難題,對系統(tǒng)模型依賴程度低,并進(jìn)一步提高了控制器的魯棒性。 本文探討的三種減搖鰭算法魯棒性依次遞增,能夠保證了閉環(huán)系統(tǒng)的穩(wěn)定性,并在后兩種算法中考慮了系統(tǒng)的輸入飽和現(xiàn)象,進(jìn)一步增強(qiáng)了系統(tǒng)的穩(wěn)定性。最后以MATLAB軟件為工具進(jìn)行仿真研究,驗證了算法的有效性。
[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.
【學(xué)位授予單位】：大連海事大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：U664.72

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