Robust control by adaptive Non-singular Terminal Sliding Mode
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- 作者：Reza Mohammadi Asl<sup>asup><sup> ; sup><sup>r.mohammadi92@ms.tabrizu.ac.irsup> ; Yashar Shabbouei Hagh<sup>asup><sup> ; sup><sup>y.shabbouei92@ms.tabrizu.ac.irsup> ; Rainer Palm<sup>bsup><sup> ; sup><sup>rub.palm@t-online.desup>
- 关键词：Artificial intelligence ; Modified charged system search ; Neural networks ; Non-singular Terminal Sliding Mode Control ; Unscented Kalman filter ; Robotic manipulator
- 刊名：Engineering Applications of Artificial Intelligence
- 出版年：2017
- 出版时间：March 2017
- 年：2017
- 卷：59
- 期：Complete
- 页码：205-217
- 全文大小：2201 K
- 卷排序：59
文摘
Based on the principles of the Non-singular Terminal Sliding Mode Control (NTSMC), a new control law along with an Unscented Kalman Filter (UKF) has been proposed for robotic manipulators, that can tolerate external disturbances and noises with unknown statistics. First, a neural network module has been used as a discontinuous control part of the NTSMC to enhance the performance of the controller due to chattering phenomenon. Furthermore, a new methodology is proposed which is based on a modified evolutionary algorithm (charged systems search) to estimate the system states by the UKF and the measurement and process noise covariances. To compare this evolutionary method with classical methods, an optimal Unscented Kalman Filter (UKF) algorithm has been introduced that estimates the noise statistics recursively within the algorithm. The proposed control method and observer have been simulated on a 6-DOF robot manipulator.