本文關(guān)鍵詞： 船舶電力推進 吊艙推進電機 矢量控制 無模型自適應控制 擾動抑制　出處：《大連海事大學》2015年博士論文　論文類型：學位論文

【摘要】：遠洋運輸是高能耗高排放的行業(yè),實現(xiàn)船舶節(jié)能減排是海運業(yè)發(fā)展的重大需求。研究船舶吊艙推進系統(tǒng)的相關(guān)控制問題,不僅對解決推進電機的運行、優(yōu)化與管理有重要的指導作用,更對實現(xiàn)海運業(yè)節(jié)能減排有重要意義。針對船舶吊艙推進控制系統(tǒng)的大慣性、強耦合、模型參數(shù)不確定以及航行中受到的風、浪、流等測量擾動及負載擾動的問題,本論文研究了基于無模型自適應矢量控制的船舶吊艙推進系統(tǒng)控制策略,具體內(nèi)容如下：針對常規(guī)船舶吊艙推進矢量控制系統(tǒng)中由于不確定性動態(tài)而存在的模型攝動問題,將無模型自適應控制算法與矢量控制方法相融合,提出一種全新的無模型自適應矢量控制算法,推導出SSP推進電機的動態(tài)線性化方程,基于速度跟蹤誤差設計了無模型自適應矢量控制器,在線調(diào)整偽偏導數(shù),保證了推進電機控制系統(tǒng)跟蹤誤差一致且有界。并通過嚴格的收斂性證明和仿真實驗論證了該方法應用于船舶吊艙推進控制系統(tǒng)的有效性。針對無模型自適應矢量控制方法僅利用過去一步采樣時刻信息的問題,在高階學習律的基礎(chǔ)上提出了一種高階無模型自適應矢量控制算法,通過設計一個新的控制輸入準則函數(shù),使得更多船舶航行過程中的控制信息得到充分利用,從而使得控制器的設計更加靈活,通過嚴格的數(shù)學證明,論證了偽偏導數(shù)估計值的有界性、系統(tǒng)穩(wěn)定收斂性以及控制輸入的有界性,仿真實驗表明所提出方法進一步提高了船舶吊艙推進控制系統(tǒng)的收斂性能。針對船舶吊艙推進系統(tǒng)由于受到外部海況等未知負載擾動,導致控制量的頻繁動作等問題,設計一種帶死區(qū)擾動補償?shù)臒o模型自適應矢量控制器,首先在無模型自適應矢量控制器控制律的更新算法中引入一個控制死區(qū),并設計了基于擴張狀態(tài)觀測器的擾動估計器,最后進行了收斂性證明,仿真實驗表明該算法可以抑制未知負載擾動的作用,避免控制量的頻繁動作對SSP推進控制系統(tǒng)執(zhí)行機構(gòu)的齒輪傳動部件的較大磨損,提高控制系統(tǒng)的魯棒性能。針對船舶吊艙推進系統(tǒng)的復雜動態(tài)特性及惡劣工作環(huán)境而帶來的測量擾動,進行了一些實際應用的推廣,研究了無模型自適應矢量控制的主動抗擾能力,提出了一種基于小波分析的無模型自適應矢量控制器,該控制器應用小波分析對輸出信號進行濾波處理,然后將處理后的信號應用于無模型自適應矢量控制算法構(gòu)造控制律,最后理論證明了當系統(tǒng)存在有界測量擾動時改進算法的穩(wěn)定性和收斂性,仿真實驗論證了該算法對于抑制測量擾動的有效性。
[Abstract]:Ocean transportation is an industry with high energy consumption and high emission. It is an important demand for marine transportation industry to realize energy saving and emission reduction. To study the control problems of ship podded propulsion system is not only to solve the operation of propulsion motor. Optimization and management play an important role in guiding the marine transportation industry to achieve energy saving and emission reduction. Aiming at the large inertia, strong coupling, model parameters uncertainty and wind in navigation of the propulsion control system of ship pods. In this paper, the control strategy of ship podded propulsion system based on modelless adaptive vector control is studied. The main contents are as follows: aiming at the model perturbation problem existing in the conventional ship podded propulsion vector control system due to the uncertain dynamics, the model-free adaptive control algorithm is combined with the vector control method. A novel model-free adaptive vector control algorithm is proposed, and the dynamic linearization equation of SSP propulsion motor is derived. The model-free adaptive vector controller is designed based on the velocity tracking error. Adjust the pseudo-partial derivative online. The tracking error of propulsion motor control system is consistent and bounded. The validity of this method applied to ship pods propulsion control system is proved by strict convergence proof and simulation experiment. The method of quantity control only uses the information of sampling time in the past step. On the basis of higher order learning law, an adaptive vector control algorithm with high order modeless is proposed. By designing a new control input criterion function, more and more control information during ship navigation are fully utilized. Through strict mathematical proof, the boundedness of pseudo-partial derivative estimator, the stability convergence of system and the boundedness of control input are proved. The simulation results show that the proposed method can further improve the convergence performance of the ship pods propulsion control system. The ship pods propulsion system is disturbed by unknown loads such as external sea conditions. In this paper, a model-free adaptive vector controller with dead-zone disturbance compensation is designed. Firstly, a dead-time control algorithm is introduced to update the control law of the model-free adaptive vector controller. A disturbance estimator based on the extended state observer is designed. Finally, the convergence is proved. The simulation results show that the proposed algorithm can suppress the unknown load disturbance. Avoid the large wear of the gear transmission parts of the actuators of the SSP propulsion control system by avoiding the frequent movement of the control quantities. Improving the robust performance of the control system. Aiming at the complex dynamic characteristics of the ship podded propulsion system and the measurement disturbance caused by the bad working environment, some practical applications are extended. The active immunity ability of model-free adaptive vector control is studied. A model free adaptive vector controller based on wavelet analysis is proposed. Wavelet analysis is used to filter the output signal. Then the processed signal is applied to the model-free adaptive vector control algorithm to construct the control law. Finally, the stability and convergence of the improved algorithm are proved when the system has bounded measurement disturbance. Simulation results demonstrate the effectiveness of the proposed algorithm in suppressing measurement disturbances.
【學位授予單位】：大連海事大學
【學位級別】：博士
【學位授予年份】：2015
【分類號】：U664.3

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