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A Novel Network Control Algorithm for Multi-Axis Manipulator Systems

机译:多轴机械手系统的新型网络控制算法

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Many researchers have studied robot system identification in recent years. Nonlinear system identification, whether, it be forward or inverse model identification, is becoming increasingly important in modern control applications. Nonlinear system identification can improve control performance significantly, especially when the system dynamic behaviors are unknown and exhibit great nonlinearity. Additionally, the network has been applied to control engineering. The concept of network simulates the concentration of a set of antibodies. The network system has the following features: self-organization, memory, recognition, adaptability and the ability of learning. Therefore, the network could be applied to nonlinear system identification and provide various feasible options for system models with robust and adaptive characteristics.
机译:近年来,许多研究人员研究了机器人系统识别。非线性系统识别,无论是正向模型识别还是逆模型识别,在现代控制应用中变得越来越重要。非线性系统识别可以显着改善控制性能,尤其是当系统动态行为未知且表现出很大的非线性时。此外,该网络已应用于控制工程。网络的概念模拟了一组抗体的浓度。该网络系统具有以下特征:自组织,记忆,识别,适应性和学习能力。因此,该网络可以应用于非线性系统识别,并为具有鲁棒性和自适应性的系统模型提供各种可行的选择。

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