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Intelligent Decoupling Control of Nonlinear Multivariable Systems and its Application to a Wind Tunnel System

机译:非线性多变量系统的智能解耦控制及其在风洞系统中的应用

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摘要

In this paper, for a class of nonlinear multivariable discrete-time systems, an open-loop approximately dynamical decoupling control law is first presented. Then, by introducing a $lambdacirc r$ difference operator, an intelligent decoupling control method using multiple models and neural networks (NNs) is developed. The intelligent decoupling control method includes a set of fixed decoupling controllers, a reinitialized NN adaptive decoupling controller, a free-running NN adaptive decoupling controller, and a switching mechanism. Theory analysis shows that the free-running NN adaptive decoupling controller can guarantee the bounded-input–bounded-output stability of the closed-loop system, while the multiple fixed decoupling controllers and the reinitialized NN adaptive decoupling controller are used to improve the system performance. To illustrate the method, the proposed design is applied to a 2.4 $times$ 2.4-m injector-driven transonic wind tunnel system. Simulation and industrial experiment results show the effectiveness and practicality of the proposed method.
机译:本文针对一类非线性多变量离散时间系统,首先提出了一种开环近似动态解耦控制律。然后,通过引入一个λλcircr$差分算子,开发了一种使用多个模型和神经网络(NN)的智能解耦控制方法。智能解耦控制方法包括一组固定的解耦控制器,一个重新初始化的NN自适应解耦控制器,一个自由运行的NN自适应解耦控制器和一个切换机制。理论分析表明,自由运行的神经网络自适应解耦控制器可以保证闭环系统的有界输入-有界输出稳定性,同时采用多个固定解耦控制器和重新初始化的神经网络自适应解耦控制器来提高系统性能。 。为了说明该方法,将所提出的设计应用于2.4倍2.4米喷油器驱动的跨音速风洞系统。仿真和工业实验结果表明了该方法的有效性和实用性。

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