本文選題：塔式起重機　切入點：滑�？刂�　出處：《太原科技大學》2012年碩士論文

【摘要】：本論文在分析國內(nèi)外塔式起重機的研究現(xiàn)狀和發(fā)展趨勢的基礎上，針對其特點和目前控制方案中存在的不足，設計出應用于塔式起重機系統(tǒng)的定位和防擺控制的新方法，保障系統(tǒng)安全、快速、運行平穩(wěn)，改善系統(tǒng)的動靜態(tài)性能，提高系統(tǒng)運行效率，實現(xiàn)負載精確定位和快速消擺。主要研究內(nèi)容如下： 首先，根據(jù)模糊滑�？刂圃�，設計了一種基于時滯濾波器的塔式起重機模糊滑模防擺控制新方法。運用滑�？刂葡撦d擺動，模糊控制對滑模趨近率參數(shù)進行調(diào)節(jié)，抑制了一般滑�？刂频亩墩瘳F(xiàn)象，并利用時滯濾波器對模型輸入進行濾波，消除不確定性系統(tǒng)的殘留振動，在存在外部干擾的情況下,實現(xiàn)對小車的定位和負載擺動的有效控制，仿真結果表明方法的有效性和可行性。 其次，在普通滑模面的基礎上設計出PD分數(shù)階滑模面，分數(shù)階滑模面的定義將使得系統(tǒng)具有較高的魯棒性和快速性，它在消除了系統(tǒng)的高頻抖振的同時，，使得滑模運動狀態(tài)保持一個較快的速度趨近至切換面。通過遺傳算法對分數(shù)階滑�？刂破髦械膮�(shù)進行了優(yōu)化,并取得較好的控制效果。 最后，通過對塔式起重機系統(tǒng)的動力學模型分析，針對塔式起重機模型參數(shù)的不確定性和在運行過程中存在的負載擺動，提出了一種神經(jīng)網(wǎng)絡滑模防擺控制新方法。利用神經(jīng)網(wǎng)絡輸出逼近系統(tǒng)的不確定項，不需要對模型進行近似解耦或線性化處理，并且考慮了系統(tǒng)所受的摩擦力等因素，存在外界干擾的情況下，系統(tǒng)仍能實現(xiàn)對臂架小車的精確定位和減少負載的擺動時間，削弱了系統(tǒng)的高頻抖振，提高了系統(tǒng)的控制性能。
[Abstract]:On the basis of analyzing the research status and development trend of tower crane at home and abroad, this paper designs a new method for positioning and anti-swing control of tower crane system according to its characteristics and shortcomings in current control scheme. Ensure the system safety, fast, smooth operation, improve the dynamic and static performance of the system, improve the operational efficiency of the system, achieve accurate load positioning and fast swing elimination. The main research contents are as follows:. Firstly, according to the principle of fuzzy sliding mode control, a new method of fuzzy sliding mode anti-swing control for tower crane based on time-delay filter is designed. The sliding mode control is used to eliminate load swing, and fuzzy control is used to adjust the parameters of sliding mode approach rate. The chattering phenomenon of general sliding mode control is suppressed, and the model input is filtered by time-delay filter to eliminate the residual vibration of uncertain system. The vehicle positioning and load swing are effectively controlled. The simulation results show that the method is effective and feasible. Secondly, the PD fractional sliding mode surface is designed on the basis of ordinary sliding mode surface. The definition of fractional sliding mode surface will make the system have higher robustness and rapidity, which not only eliminates the high frequency buffeting of the system, but also eliminates the high frequency buffeting of the system. The sliding mode motion state is kept close to the switching surface at a faster speed, and the parameters of the fractional sliding mode controller are optimized by genetic algorithm, and a good control effect is obtained. Finally, by analyzing the dynamic model of the tower crane system, the uncertainty of the model parameters and the load swing in the running process of the tower crane are analyzed. In this paper, a new method of neural network sliding mode anti-swing control is proposed. It is not necessary to approximate decouple or linearize the model by using neural network output to approximate the uncertainty of the system, and the friction force of the system is taken into account. In the presence of external interference, the system can still achieve accurate positioning of the boom trolley and reduce the load swing time, weaken the high frequency buffeting of the system, and improve the control performance of the system.
【學位授予單位】：太原科技大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TH213.3

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