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New Smith Internal Model Control of Two-Motor Drive System Based on Neural Network Generalized Inverse

机译:基于神经网络通用逆的双电机驱动系统新史密斯内部模型控制

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摘要

Multimotor drive system is widely applied in industrial control system. Considering the characteristics of multi-input multioutput, nonlinear, strong-coupling, and time-varying delay in two-motor drive systems, this paper proposes a new Smith internal model (SIM) control method, which is based on neural network generalized inverse (NNGI). This control strategy adopts the NNGI system to settle the decoupling issue and utilizes the SIM control structure to solve the delay problem. The NNGI method can decouple the original system into several composite pseudolinear subsystems and also complete the pole-zero allocation of subsystems. Furthermore, based on the precise model of pseudolinear system, the proposed SIM control structure is used to compensate the network delay and enhance the interference resisting the ability of the whole system. Both simulation and experimental results are given, verifying that the proposed control strategy can effectively solve the decoupling problem and exhibits the strong robustness to load impact disturbance at various operations.
机译:多电机驱动系统被广泛地应用在工业控制系统。考虑多输入多输出,非线性,强耦合,并随时间变化的在双电机延迟驱动系统的特性,提出了一种新的史密斯内部模型(SIM)的控制方法,它是基于神经网络的广义逆( NNGI)。这种控制策略采用NNGI系统解决的问题脱钩,并利用SIM控制结构来解决延迟问题。该方法NNGI可以断开此原始系统分成多个复合伪线性子系统并同时完成子系统的零极点分配。此外,基于伪线性系统的精确模型,所提出的SIM控制结构被用于补偿网络延迟和提高耐干扰整个系统的能力。无论仿真和实验结果给出,验证所提出的控制策略可以有效地解决问题的解耦,并在各种操作具有较强的鲁棒性负载冲击扰动。

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