五自由度机器人的离散时间分散神经反步控制器

2009 17th Mediterranean Conference on Control and Automation Pub Date : 2009-06-24 DOI:10.1109/MED.2009.5164600

R. García-Hernández, E. Sánchez, M. Saad, E. Bayro-Corrochano

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引用次数: 0

摘要

针对五自由度机器人的自适应轨迹跟踪问题，采用高阶神经网络(HONN)逼近由步进法设计的分散控制律，并将其应用于块严格反馈形式(BSFF)。通过扩展卡尔曼滤波(EKF)算法在线学习HONN。通过仿真验证了该方案的适用性。

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Discrete-time decentralized neural backstepping controller for a five DOF robot manipulator

This paper deals with adaptive trajectory tracking for a five DOF robot manipulator, 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 applicability of the proposed scheme is illustrated via simulations.

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2009 17th Mediterranean Conference on Control and Automation

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