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本文将神经网络快速计算的性能应用于广义预测控制中,以便克服广义预测控制算法的不足之处。仿真研究表明,这种方法实为改进控制算法性能的有效途径。
In this paper, the performance of neural network fast computation is applied to generalized predictive control in order to overcome the shortcomings of the generalized predictive control algorithm. Simulation studies show that this method is actually an effective way to improve the performance of control algorithm.