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Neural networks and genetic algorithms for dynamic systems control

机译:用于动态系统控制的神经网络和遗传算法

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This paper deals with the predictive control strategy of non linear dynamic systems based on Artificial Neural Networks and Genetic Algorithms (GAs). The Feed Forward Neural Networks (FFNN) is used to obtain the model of the process. The control action is provided by minimizing a control objective which is function of the future prediction output and the future control actions. The optimization is carried out using GAs. The proposed control scheme is applied to numerical problems and the simulation results are included.
机译:本文涉及基于人工神经网络和遗传算法(气体)非线性动态系统的预测控制策略。前馈神经网络(FFNN)用于获得该过程的模型。通过最小化作为未来预测输出的功能和未来控制动作的功能来提供控制动作。优化使用气体进行。所提出的控制方案应用于数值问题,并且包括模拟结果。

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