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Self-tuning control of non-linear servomotor: Standard versus dual approach

机译:非线性伺服电机的自整定控制:标准方法与双重方法

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摘要

The majority of processes met in the industrial practice have stochastic characteristics and eventually they embody non-linear behaviour. Traditional controllers with fixed parameters are often unsuitable for such processes because their parameters change. The changes of process parameters are caused by changes in the manufacturing process, in the nature of the input materials, fuel, machinery use (wear) etc. Fixed controllers cannot deal with this. One possible alternative for improving the quality of control for such processes is the use of adaptive control systems. Different approaches were proposed and utilized. One successful approach is represented by self-tuning controller (STC). This approach is also called system with indirect adaptation (with direct identification). The main idea of an STC is based on the combination of a recursive identification procedure and a selected controller synthesis. Presently, most of the STCs are based on the Certainty Equivalence (CE) Principle, which is only suboptimal. One of the possibilities to improve the quality of these adaptive control methods is usage of an Adaptive Dual Control (the bicriterial approach). In this paper, the bicriterial approach is verified and compared with some other adaptive control approaches based on the CE Principle by the real-time control of a highly non-linear laboratory model, the DR300 Speed Control with Variable Load.
机译:工业实践中满足的大多数过程具有随机特征,最终体现为非线性行为。具有固定参数的传统控制器通常不适合此类过程,因为它们的参数会发生变化。工艺参数的变化是由制造工艺的变化,输入材料,燃料,机械使用(磨损)等的性质引起的。固定控制器无法对此进行处理。用于改善此类过程的控制质量的一种可能的替代方法是使用自适应控制系统。提出并利用了不同的方法。一种成功的方法是自调整控制器(STC)。这种方法也称为具有间接适应性(直接识别)的系统。 STC的主要思想是基于递归识别过程和所选控制器综合的结合。当前,大多数STC都基于确定性对等(CE)原则,这只是次优的。改善这些自适应控制方法质量的一种可能性是使用自适应双重控制(双向方法)。本文通过对高度非线性实验室模型的实时控制(可变负载DR300速度控制),对双标准方法进行了验证,并将其与其他基于CE原理的自适应控制方法进行了比较。

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