A synthesis of classical and adaptive control

L. J. Brown, Sean P. Meyn
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引用次数: 4

Abstract

In this paper we describe a new adaptive control algorithm which is specifically designed for for systems which are difficult to control. The models that we consider may exhibit nontrivial time variations; have significant delays; have nonminimum phase characteristics; and may be subject to measurement noise and plant disturbances. Our goal is to obtain robust control laws, and to simultaneously obtain good transient response and small steady state error. A two step procedure is taken. First, we design a linear controller which is based on some a priori knowledge of the plant. This controller incorporates predictions of future outputs which are obtained from online parameter estimates. It is argued that this makes the design of a robust controller easier than when predictions are not used. Secondly, the control law feeds back filtered estimates of the disturbance process, which are also obtained from the parameter estimator online. An optimal design technique is used to design an appropriate filter, thereby tuning the disturbance response of the closed loop system. A robotic welder at the Construction Engineering Research Laboratory in Champaign, Illinois is currently being used as a test bed for these theoretical results. Observations are described and future work is discussed.<>
经典控制与自适应控制的综合
本文提出了一种新的自适应控制算法,该算法是专门针对难以控制的系统而设计的。我们考虑的模型可能表现出非平凡的时间变化;有重大延误;具有非最小相位特性;并且可能受到测量噪声和植物干扰。我们的目标是获得鲁棒控制律,同时获得良好的瞬态响应和小的稳态误差。这个过程分为两步。首先,我们设计了一个基于被控对象先验知识的线性控制器。该控制器结合了从在线参数估计中获得的未来输出的预测。有人认为这使得鲁棒控制器的设计比不使用预测时更容易。其次,控制律在线反馈扰动过程的滤波估计,这些估计也是由参数估计器获得的。采用优化设计技术设计合适的滤波器,从而对闭环系统的扰动响应进行调谐。伊利诺斯州尚佩恩市建筑工程研究实验室的一个机器人焊工目前正被用作这些理论结果的试验台。对观察结果进行了描述,并讨论了今后的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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