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Nonlinear Adaptive Direct Generalized Predictive Control Based on LS-SVR Algorithm

机译:基于LS-SVR算法的非线性自适应直接广义预测控制

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Learning the multi-step forecast optimization strategy from Dynamic Matrix Control (DMC) and Model Algorithmic Control (MAC), Generalized Predictive Control (GPC) has a strong ability to overcome load disturbance, random noise and delay change, and the selected model has less parameter, so it is easy to control. But it also has some problems such as big amount of calculation and no consideration to both rapidity and over modulation. So an adaptive direct GPC method is proposed based on LS-SVR and tracking error. This method uses LS-SVR method to design predictive controller, and uses a modified projection algorithm, based on tracking error, to adjust the weight of LS-SVR adaptively, in order to avoid calculating the inverse matrix. The result indicates that the method not only is very effective but also reduces the calculation amount.
机译:从动态矩阵控制(DMC)和模型算法控制(MAC)学习多步预测优化策略,广义预测控制(GPC)具有强大的能力来克服负载扰动,随机噪声和时延变化,并且所选模型较少参数,因此易于控制。但是它也有一些问题,例如计算量大,没有同时考虑速度和过调制。因此,提出了一种基于LS-SVR和跟踪误差的自适应直接GPC方法。该方法采用LS-SVR方法设计预测控制器,并基于跟踪误差采用改进的投影算法,自适应地调整LS-SVR的权重,从而避免计算逆矩阵。结果表明,该方法不仅非常有效,而且减少了计算量。

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