塔式起重机智能防摆和定位控制方法研究

【作者】 孙辉；

【导师】 陈志梅；

【作者基本信息】 太原科技大学 ， 控制理论与控制工程， 2012， 硕士

【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。更多还原

【Abstract】 Based on the analysis of the current research status and developmenttendency of crane indoors and outdoors, according to the characteristics of towercrane system and the disadvantages of the current control method, the newpositioning and anti-swing control is designed for the intelligent tower cranesystem so as to obtain the performances of absolute safety, fast speed andsmooth operation, improve the dynamic and static, increase system efficiency,and obtain precise positioning and quick anti-swing. The main contents are asfollows:Firstly, based on time-delayed filter and the fuzzy sliding mode controltheory, a new method of fuzzy sliding mode anti-swing control is proposed fortower crane. This method, which consists the sliding mode control to eliminatethe load swing and the fuzzy control to adjust the parameters of reaching law,weakens or avoids the chattering and improves the rate when the system reachesthe sliding surface. And the time-delayed filter which could filter the modelinput signal is designed to reduce residual vibration in the uncertain system. Thismethod enables the system to have good dynamic performances and enhancesthe quality of control system. The simulation results show the feasibility andeffectiveness of the method.Secondly, the PD fractional sliding surface on the basis of the commonsliding surface is designed, where the definition of fractional sliding surface hasa high robustness and fast speed so as to reduce the chattering phenomenon insliding mode control (SMC) and lead to maintain a faster speed to reach thesliding surface. Genetic algorithm is used to determine and optimize theparameters of fractional sliding mode controller (FSMC). The simulation resultsshow that the method obtains better control effect.Finally, through the force analysis for tower crane system, a new neuralnetwork sliding mode control method is formulated for the uncertainties of cranemodel parameters. The neural network is adopted to approximate theuncertainties of system, and considering the friction of system, it is needless to approximately decouple or exactly linearize the model of tower crane, and thecontroller can accurately position the trolley, suppress the payload swing even inthe presence of parameters uncertainties and external disturbance and improvethe control performance of the system.更多还原