机器人操纵臂的实时分散神经反步控制器

2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC) Pub Date : 2009-07-08 DOI:10.1109/CCA.2009.5280998

R. García-Hernández, E. Sánchez, V. Santibáñez, M. Llama, E. Bayro-Corrochano

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引用次数: 3

摘要

研究了离散多输入多输出非线性系统的自适应轨迹跟踪问题。采用高阶神经网络(HONN)对应用于块严格反馈形式(BSFF)的反步技术设计的分散控制律进行逼近。通过扩展卡尔曼滤波(EKF)算法在线学习HONN。将该方法应用于二自由度机器人的实时控制。

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Real-time decentralized neural backstepping controller for a robot manipulator

This paper deals with adaptive trajectory tracking for discrete-time MIMO nonlinear systems. A high order neural network (HONN) is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feedback form (BSFF). The HONN learning is performed online by an Extended Kalman Filter (EKF) algorithm. The proposed scheme is implemented in real-time to control a two DOF robot manipulator.

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来源期刊

2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)

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