塔式起重机智能防摆和定位控制方法研究

发布时间：2018-03-23 13:27

本文选题：塔式起重机　切入点：滑模控制　出处：《太原科技大学》2012年硕士论文

【摘要】：本论文在分析国内外塔式起重机的研究现状和发展趋势的基础上，针对其特点和目前控制方案中存在的不足，设计出应用于塔式起重机系统的定位和防摆控制的新方法，保障系统安全、快速、运行平稳，改善系统的动静态性能，提高系统运行效率，实现负载精确定位和快速消摆。主要研究内容如下：首先，根据模糊滑模控制原理，设计了一种基于时滞滤波器的塔式起重机模糊滑模防摆控制新方法。运用滑模控制消除负载摆动，模糊控制对滑模趋近率参数进行调节，抑制了一般滑模控制的抖振现象，并利用时滞滤波器对模型输入进行滤波，消除不确定性系统的残留振动，在存在外部干扰的情况下,实现对小车的定位和负载摆动的有效控制，仿真结果表明方法的有效性和可行性。其次，在普通滑模面的基础上设计出PD分数阶滑模面，分数阶滑模面的定义将使得系统具有较高的鲁棒性和快速性，它在消除了系统的高频抖振的同时，，使得滑模运动状态保持一个较快的速度趋近至切换面。通过遗传算法对分数阶滑模控制器中的参数进行了优化,并取得较好的控制效果。最后，通过对塔式起重机系统的动力学模型分析，针对塔式起重机模型参数的不确定性和在运行过程中存在的负载摆动，提出了一种神经网络滑模防摆控制新方法。利用神经网络输出逼近系统的不确定项，不需要对模型进行近似解耦或线性化处理，并且考虑了系统所受的摩擦力等因素，存在外界干扰的情况下，系统仍能实现对臂架小车的精确定位和减少负载的摆动时间，削弱了系统的高频抖振，提高了系统的控制性能。
[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.
【学位授予单位】：太原科技大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TH213.3

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