首页> 外文会议>IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th >Interdependent multiobjective control using Biased Neural Network (Biased NN)
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Interdependent multiobjective control using Biased Neural Network (Biased NN)

机译:使用偏置神经网络的相互依赖多目标控制(偏置神经网络)

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A Biased Neural Network (Biased-NN) is proposed to solve an interdependent multiobjective control problem. The main idea of the Biased-NN stems from a decoupled fuzzy sliding mode control scheme that provides a simple way to achieve asymptotic stability for a class of decoupled systems. Each neuron in the Biased-NN is used to approximate a sign function in order to replace the sliding mode control structure with the Biased-NN. Such a feature is useful for handling the interdependent multiobjective control problem based upon the proposed supporting strategy. While previous works require a priori knowledge for all the objectives, the proposed method uses only expert knowledge of the objective that is considered the main concern. Simulations are conducted to show the effectiveness of the Biased-NN.
机译:提出了一种有偏神经网络(Biased-NN)来解决相互依赖的多目标控制问题。 Biased-NN的主要思想源于解耦模糊滑模控制方案,该方案为一类解耦系统提供了一种实现渐近稳定性的简单方法。 Biased-NN中的每个神经元都用于近似符号函数,以便用Biased-NN代替滑模控制结构。基于建议的支持策略,此功能对于处理相互依赖的多目标控制问题很有用。尽管先前的工作要求所有目标都具有先验知识,但是所提出的方法仅使用被认为是主要关注目标的专家知识。进行仿真以显示Biased-NN的有效性。

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