The purpose of this paper is to study the controller design of flexible manipulator. Flexible manipulator system is a nonlinear, strong coupling, time-varying system, which is introduced elastodynamics in the study and complicated to control. However, due to the flexible manipulator, system has a significant advantage in response speed, control accuracy and load weight ratio to attract a lot of researchers.
Since the order of flexible manipulator system is high, designing controller process will be complex, and have a large amount of calculation, but this paper will use the dynamic surface control method to solve this problem.
Dynamic surface control method as a controller design method which can effectively solve the problem with the system contains nonlinear and reduced design complexity.
The authors assume that the dynamic parameters of flexible manipulator system are unknown, and use Radial Basis Function neural network to approach the unknown system, combined with the dynamic surface control method to design the controller.
This work was partially supported by National Nature Science Foundation (NSFC) under Grant 61473120, Guangdong Provincial Natural Science Foundation 2014A030313266 and International Science and Technology Collaboration Grant 2015A050502017, Science and Technology Planning Project of Guangzhou 201607010006, State Key Laboratory of Robotics and System (HIT) Grant SKLRS-2017-KF-13 and the Fundamental Research Funds for the Central Universities.
Chen, Z., Yang, C., Liu, X. and Wang, M. (2017), "Learning control of flexible manipulator with unknown dynamics", Assembly Automation, Vol. 37 No. 3, pp. 304-313. https://doi.org/10.1108/AA-11-2016-148Download as .RIS
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