Identification and Control of Flexible Joint Robot Using Multi-Time-Scale Neural Network
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Identification and Control of Flexible Joint Robot Using Multi-Time-Scale Neural Network
Üýý),
ZHENG Dongdong1 (
LI Pengcheng1,2 (
), XIE Wenfang1∗ (
DZ),
LI Dan3 (
)
(1. Department of Mechanical, Industrial & Aerospace Engineering, Concordia University, Montreal H3G 1M8, Canada; 2. College of Mechanical & Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; 3. Department of Electrical and Computer Engineering, Concordia University, Montreal H3G 1M8, Canada)
© Shanghai Jiao Tong University and Springer-Verlag GmbH Germany, part of Springer Nature 2020 Abstract: In this paper, a new identification and control scheme for the flexible joint robotic manipulator is proposed. Firstly, by defining some new state variables, the commonly used dynamic equations of the flexible joint robotic manipulators are transformed into the standard form of a singularly perturbed model. Subsequently, an optimal bounded ellipsoid algorithm based identification scheme using multi-time-scale neural network is proposed to identify the unknown system dynamic equations. Lastly, by using the singular perturbation theory, an indirect adaptive controller based on the identified model is proposed to control the system such that the joint angles can track the given reference signals. The closed-loop stability of the whole system is proved, and the effectiveness of the proposed schemes is verified by simulations. Key words: flexible joint, robotic manipulator, multi-time-scale neural network, singular perturbation, adaptive controller CLC number: TP 242 Document code: A
0 Introduction Nowadays, the industrial robots are widely used in manufacturing industry to achieve higher accuracy and efficiency. During the system analysis and controller design process, it is usually assumed that the robotic manipulators consist only of rigid bodies. However, when motion transmission/reduction elements such as belts, long shafts, cables, harmonic drives or cycloidal gears are used, the joint flexibility will present. If the flexibility is not considered during the robot and controller design process, the overall expected performance of the robot typically degrades[1]. So far, different methods have been presented in literature to control the flexible joint robotic manipulators. Early results can be found in Refs. [2-4]. In Ref. [5], two approaches for compensating the nonlinear joint torsion with hysteresis of a flexible joint robotic manipulator were described and compared with each other. In Ref. [6], a genetic algorithm based approach was developed to find an optimized trajectory in joint space for a plane-flexible joint manipulator and to reduce the residual vibration of the robot on the occasion of fast Received date: 2020-01-15 Foundation item: the Natural Sciences and Engineering Research Council of Canada (No. N00892) ∗E-mail: [email protected]
position control. In Ref. [7], a composite controller was proposed by the feedback linearisation and singular perturbation approach for a flexible beam consisting o
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