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首页> 外文期刊>Journal of Control Engineering and Applied Informatics >Adaptive Iterating learning sliding mode control for output tracking of incommensurate fractional-order systems
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Adaptive Iterating learning sliding mode control for output tracking of incommensurate fractional-order systems

机译:不匹配分数阶系统的输出跟踪的自适应迭代学习滑模控制

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This paper develops a novel controller called adaptive iterative learning sliding mode (AILSM) to control linear and nonlinear incommensurate fractional-order systems. This control applies a hybrid structure of adaptive and iterative learning control into sliding mode method. It can switch between both adaptive and iterative learning control in order to use the advantage of both controller simultaneously and therefore achieve better control performance. This controller is designed in the way to be robust against the external disturbance. It also estimates unknown parameters of fractional-order systems. The proposed controller unlike the conventional iterative learning control for fractional systems does not need to apply direct control input to output of the system and also implemented for incommensurate fractional-order systems. It is shown that the controller perform well in partial and complete observable conditions. Illustrative examples verifies the performance of the proposed control in presence of unknown disturbances and model uncertainties
机译:本文开发了一种新颖的控制器,称为自适应迭代学习滑模(AILSM),用于控制线性和非线性不等分数阶系统。该控制将自适应和迭代学习控制的混合结构应用到滑模方法中。它可以在自适应学习控制和迭代学习控制之间切换,以便同时利用两个控制器的优势,从而获得更好的控制性能。该控制器经过精心设计,可以抵抗外部干扰。它还估计分数阶系统的未知参数。所提出的控制器与分数系统的常规迭代学习控制不同,它不需要将直接控制输入应用于系统的输出,也不需要为不相称的分数阶系统实现。结果表明,控制器在部分和完全可观察的条件下表现良好。说明性示例验证了存在未知干扰和模型不确定性的情况下所提出控制的性能

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