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引用次数: 1

摘要

控制律划分是一种广泛应用的概念,它将被控对象的数学模型纳入控制系统。这既是优点也是缺点。有了一个精确的模型,系统控制就会更加鲁棒和易于管理。然而,对于一个复杂的非线性系统,精确的数学模型很难得到。可以开发一种模糊逻辑控制器,利用经验导出的数据,从而准确地对工厂建模,而不需要数学模型。将这样的控制器调整到经验数据可能会有问题,因此使用调谐算法来调整控制器参数以获得最佳性能。本文以一个四阶系统为示范对象,采用快速离线整定算法设计了模糊控制器,并对控制器的性能进行了检验。
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Control law partitioning via fuzzy logic control
Control law partitioning is a widely used concept that incorporates a mathematical model of the plant into the control system. This is both an advantage and disadvantage. With an accurate model, the system control is much more robust and easy to manage. However, with a complex nonlinear system, an accurate mathematical model can be very difficult to obtain. A fuzzy logic controller can be developed that makes use of empirically derived data thereby accurately modeling the plant without the necessity of a mathematical model. Tuning such a controller to the empirical data can be problematic, so a tuning algorithm is used to adjust the controller parameters for optimal performance. In this paper, a fourth-order system is used as a demonstration plant, a fuzzy logic controller is developed using a very fast offline tuning algorithm, and the performance of the resulting controller is examined.
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