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Performance guarantees and performance optimization of MRAC for non-minimum phase systems

机译:非最小相位系统的MRAC的性能保证和性能优化

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Non-minimum phase systems pose a challenge in the design of MRAC. While some methods that can handle non-minimum phase systems are available in the literature, it is not always easy to guarantee tracking performance with these methods. This paper offers a partial solution to this problem. The method of generating an augmented plant by adding some dynamics in parallel to the original plant is used to make the adaptation scheme see a minimum phase system. The drawback of this method is that the error between original plant and original reference model does not asymptotically converge to zero, and even analysis of this error is not available in the literature. This paper offers a way to find an upper bound on the tracking error and design an alternative reference model to minimize the error. The application of the new reference model leads to improved tracking performance with respect to the original reference model. The alternative reference model is designed by iteratively solving linear matrix inequalities. Performance guarantees are given in terms of an ???2-gain bound from the reference to the tracking error, and this ???2-gain bound is minimized when the matrix inequalities are solved. An aerospace example is given to illustrate the effectiveness of our approach.
机译:非最小相位系统对MRAC的设计提出了挑战。尽管文献中提供了一些可以处理非最小相位系统的方法,但是用这些方法来保证跟踪性能并不总是那么容易。本文为该问题提供了部分解决方案。通过与原始植物并行添加一些动力学来生成增强植物的方法,用于使自适应方案具有最小相位系统。该方法的缺点是原始工厂和原始参考模型之间的误差不会渐近收敛到零,甚至在文献中也无法对此误差进行分析。本文提供了一种方法,可以找到跟踪误差的上限,并设计一种替代性的参考模型以最大程度地减小误差。新参考模型的应用导致相对于原始参考模型的改进的跟踪性能。通过迭代求解线性矩阵不等式来设计替代参考模型。性能保证是根据从参考到跟踪误差的2增益范围给出的,当解决矩阵不等式时,将2增益范围最小化。给出了一个航空航天实例来说明我们方法的有效性。

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