【作者】 王伟；

【导师】 赵新龙；

【作者基本信息】 浙江理工大学 ， 控制理论与控制工程， 2013， 硕士

【摘要】 压电陶瓷、记忆合金等智能材料构成的微执行器具有控制精度高、稳定性好等优点而被广泛应用于微电子制造、光纤通信、航空航天等重要领域。但是这些智能材料本身存在的迟滞特性不仅会降低系统的控制精度，甚至会直接影响到系统的稳定性，因此消除迟滞非线性是微纳米控制系统的首要问题。在迟滞非线性的补偿方面，最常用的方法就是建立迟滞逆模型，并将迟滞逆模型与迟滞非线性串联起来抵消迟滞非线性对系统的影响；在迟滞非线性系统的控制方面，由于其复杂性使得经典控制理论和现代控制理论都难以对其实现有效的控制。迭代学习控制是一个具有严格数学描述的智能控制方法，其控制过程不需要依赖动态系统精确的系统模型就能以简单的方式处理一些非线性、强耦合、难以建模的系统，近年来被用于迟滞非线性系统控制中。因此本文在迟滞非线性的补偿方面对Bouc-wen模型采用了逆补偿控制、在控制方面设计了两种迭代学习控制方案：1）对一类速率相关的迟滞非线性模型Bouc-wen迟滞模型求取了其精确的迟滞逆模型并运用该逆模型进行逆补偿控制。分别通过开环逆补偿控制和基于逆补偿的PID控制两种控制方案，结果显示基于逆补偿的PID控制效果比开环逆补偿控制效果更明显。2)将一类复杂的迟滞模型加于一正则系统前，迟滞的输出作为系统的输入。采用P型学习律来修正系统输入，并适当的选取了P型学习律的增益矩阵，保证了迭代学习的严格收敛性，系统能快速有效的消除迟滞非线性对系统的影响。3)对一类带有迟滞驱动的非线性系统，基于一种仅依靠输入输出数据的线性化法，提出了一种最优迭代学习控制法，不需要被控系统的逆动态模型，利用上一次迭代的输入输出数据来估计学习增益，而且在学习过程中学习增益和控制输入序列都不断修正，有效的提高了系统的跟踪性能。更多还原

【Abstract】 The smart materials such as piezoceramic, shape mamory alloys are widely used in someimportant area such as microelectronics manufacture, fibre-optical communication because oftheir high qualities.However, hysteresis that exists in these materials can result in the degradationof system performance and even lead to instability. So, it’s an important object to eliminate thehysteresis.In order to compensate the influence caused by hysteresis,the most common approach is toconstruct the inverse model cascaded with hysteresis. The inverse hysteresis models aredeveloped for the above-mentioned hysteresis respectively. On the other hand, it’s difficult tocontrol the systems with hysteresis using the classical control theory or modern control becauseof the special structure of hysteresis. ILC(Iterative learning control) is one of the intelligentcontrol methods with strict mathematical description. ILC don’t need the accurate model of thedynamic system,it can deal with some nonlinear, strong coupling systems. So it is used in thecontrol of hysteresis systems recently. This paper use a hysteresis inverse and design two ILCscheme to eliminate the effects caused by hysteresis:1)A new hysteresis inverse which is related to the rate is obtained for the Bouc-wen modeland used to efficiently compensate the hysteresis effects when developing the open loop withinverse compensation and PID control with inverse comensation. The results indicate that by PIDcontrol with inverse comensation we can obtain better precision.2)A complicated hysteresis adds to the canonical system, the output of the hysteresis is theinput of the canonical system. The P-type law is used to update the input of the system and aappropriate coefficient matrix is choosed to ensure the convergence of the system. This methodcan improve the tracking precision an eliminate the influence caused by hysteresis.3)Optimal iterative learning control for a class of nonlinear discrete-time systems withhysteresis is studied. In the control scheme, an approximating linearization model is given. Thismethod don’t need the inverse of the dynamic system, use the input and output data of the lastiteration. In the learning process, the learning gain and the sequence of the input are updating.更多还原