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Adaptive Inverse Control based on online SVR

机译:基于在线SVR的自适应逆控制

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摘要

At present, the control of a dynamic system is generally done by means of feedback. This paper proposes a new method that use online SVR to achieve feedforward control for both linear and nonlinear plants. Online SVR is a new method when a new sample is added to (or removed from) the training set, it didn't need retraining from scratch for each new data point. Therefore, it is an efficient algorithm. It has some advantages such as low computation, good approximation properties and so on. The Simulation results given in this paper shows that the algorithm has good control performance.
机译:目前,动态系统的控制通常是通过反馈来完成的。本文提出了一种使用在线SVR实现线性和非线性工厂前馈控制的新方法。当将新样本添加到训练集中(或从训练集中删除)时,在线SVR是一种新方法,不需要为每个新数据点从头开始进行训练。因此,这是一种有效的算法。它具有一些优点,例如计算量低,近似属性好等。本文给出的仿真结果表明该算法具有良好的控制性能。

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