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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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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,通常通过反馈进行动态系统的控制。本文提出了一种使用在线SVR来实现线性和非线性工厂的前馈控制的新方法。在线SVR是一种新方法,当添加到培训集(或从)训练集时,它不需要从划痕中删除每个新数据点。因此,它是一种有效的算法。它具有一些优点,如低计算,良好的近似特性等。本文中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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