Adaptive Skew Force Free Model-Based Synchronous Control and Tool Center Point Calibration for a Hybrid 6-DoF Gantry-Robot Machine

Luo, Ren C.; Perng, Yi Wen

doi:10.1109/tmech.2020.2971906

Cited by 20 publications

(8 citation statements)

References 25 publications

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“…Luo and others proposed a new time-frequency convolution neural network (TFCNN) framework, which convolutes the feature space in both time and frequency scales. Under all test conditions, for all feature sets, the performance of the framework is always better than the convolution neural network, which can significantly reduce the word error rate (WER) [5]. Zhang and others proposed an end-to-end automatic speech recognition model for mono-multispeaker on ICASSP (International Conference on Acoustics, Speech and Signal Processing).…”

Section: Literature Reviewmentioning

confidence: 99%

Design of Intelligent Speech Translation System Based on Deep Learning

Tan

2022

Mobile Information Systems

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In order to solve the problem of low translation accuracy caused by complex sentence parameters in traditional machine translation systems, a method based on deep learning was proposed. First, MCU SPCE061A is used to study the problem of complex digital signal. The training data in the synchronous translation server support the translation services of a large number of users, and the translation results were displayed through the session interface of the user terminal. The PMDL model is used to detect the keyword signal, record the PCM audio data, and slice the collected pulse code modulation signal, so as to wake up the artificial intelligence voice service. Then, this study establishes a speech recognition process that accurately outputs the speech-related semantics. In this paper, a manual interactive synchronous translation program is designed with the input text as the search criterion, and the set is trimmed to obtain the best translation effect. The experimental results show that the sentence translation accuracy of the system is 0.9 ∼ 1.0. It is proved that the method based on deep learning solves the problem of low accuracy of the traditional translation system.

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Section: Literature Reviewmentioning

confidence: 99%

Design of Intelligent Speech Translation System Based on Deep Learning

Tan

2022

Mobile Information Systems

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“…For nonlinear systems, the dynamics of the nonlinear function of the system must be identified before designing Moreover, the authors designed a neural network sliding mode controller for hybrid electric vehicles [28]. Using the Szász-Mirakyan operator as the basic function and by adjusting the polynomial coefficients through the adaptive law determined through stability analyses, a robust adaptive controller was designed to enhance the impedance control of a robot manipulator [29]. Other common methods to enhance the estimation performance include the use of neuro-fuzzy model auxiliary filters and time-varying parameters [30][31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

“…The force obtained by the force sensor is highly accurate. If the mass of the work object can be obtained considering the force of the arm and boom, the moment of inertia can be corrected to obtain more accurate moment of inertia parameters.The dynamic model for a system composed of booms, arms and folkgloves is[29]…”

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confidence: 99%

Parameter Adaptive Sliding Mode Trajectory Tracking Strategy with Initial Value Identification for the Swing in a Hydraulic Construction Robot

Hou

Zhao

Zhang

2022

Preprint

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A novel trajectory tracking strategy is developed for a double actuated swing in a hydraulic construction robot. Specifically, a nonlinear hydraulic dynamics model of a double actuated swing is established, and a robust adaptive control strategy is designed to enhance the trajectory tracking performance. When an object is grabbed and unloaded, the inertia of a swing considerably changes, and the performance of the estimation algorithm is generally inadequate. Thus, it is necessary to establish an algorithm to identify the initial value of the moment of inertia of the object. To this end, this paper proposes a novel initial value identification algorithm based on a two-DOF robot gravity force identification method combined with computer vision information. The performance of the identification algorithm is enhanced. Simulations and experiments are performed to verify the effect of the novel control scheme.

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“…Gantry robots have been widely used in manufacturing industries such as highprecision motion control, precision manufacturing, circuit assembly, microelectronics, and inspection [1][2][3]. The gantry robot is composed of a manipulator on an overhead system, and two motors are installed on two parallel linear guides to drive the moving platform.…”

Section: Introductionmentioning

confidence: 99%

Model Reference Adaptive Control and Fuzzy Neural Network Synchronous Motion Compensator for Gantry Robots

Chen

2021

Energies

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A model reference adaptive control and fuzzy neural network (FNN) synchronous motion compensator for a gantry robot is presented in this paper. This paper proposes the development and application of gantry robots with MRAC and FNN online compensators. First, we propose a model reference adaptive controller (MRAC) under the cascade control method to make the reference model close to the real model and reduce tracking errors for the single axis. Then, a fuzzy neural network compensator for the gantry robot is proposed to compensate for the synchronous errors between the dual servo motors to improve precise movement. In addition, an online parameter training method is proposed to adjust the parameters of the FNN. Finally, the experimental results show that the proposed method improves the synchronous errors of the gantry robot and demonstrates the methodology in this paper. This study also successfully integrates the hardware and successfully verifies the proposed methods.

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Adaptive Skew Force Free Model-Based Synchronous Control and Tool Center Point Calibration for a Hybrid 6-DoF Gantry-Robot Machine

Cited by 20 publications

References 25 publications

Design of Intelligent Speech Translation System Based on Deep Learning

Design of Intelligent Speech Translation System Based on Deep Learning

Parameter Adaptive Sliding Mode Trajectory Tracking Strategy with Initial Value Identification for the Swing in a Hydraulic Construction Robot

Model Reference Adaptive Control and Fuzzy Neural Network Synchronous Motion Compensator for Gantry Robots

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