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Decentralized sliding mode adaptive controller design based on fuzzy neural networks for interconnected uncertain nonlinear systems

机译:关联不确定非线性系统的模糊神经网络分散滑模自适应控制器设计。

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摘要

A new type controller, fuzzy neural networks sliding mode controller (FNNSMC), is developed for a class of large-scale systems with unknown bounds of high-order interconnections and disturbances. Although sliding mode control is simple and insensitive to uncertainties and disturbances, there are two main problems in the sliding mode controller (SMC): control input chattering and the assumption of known bounds of uncertainties and disturbances. The FNNSMC, which incorporates the fuzzy neural networks (FNNs) and the SMC, can eliminate the chattering by using the continuous output of the FNN to replace the "discontinuous" sign term in the SMC. The bounds of uncertainties and disturbances are also not required in the FNNSMC design. Two examples are presented to support the validity of the new controller. The simulation results show that the FNNSMC is more robust than the SMC.
机译:针对一类高阶互连和扰动边界未知的大型系统,开发了一种新型的控制器,模糊神经网络滑模控制器(FNNSMC)。尽管滑模控制很简单并且对不确定性和干扰不敏感,但是滑模控制器(SMC)中存在两个主要问题:控制输入颤动和不确定性和干扰的已知边界的假设。融合了模糊神经网络(FNN)和SMC的FNNSMC可以通过使用FNN的连续输出来替换SMC中的“不连续”符号项来消除抖动。 FNNSMC设计也不需要不确定性和干扰的界限。给出了两个示例来支持新控制器的有效性。仿真结果表明,FNNSMC比SMC具有更强的鲁棒性。

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