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Po Hao Huang

Bio: Po Hao Huang is an academic researcher from National Chiao Tung University. The author has contributed to research in topics: Iterative learning control & Motion control. The author has an hindex of 1, co-authored 1 publications receiving 17 citations.

Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors proposed using a computed torque controller and the disturbance observer (DOB) to robustly linearize the dynamics of robot manipulators, and the PD feedback controller is then applied for each joint to achieve the desired bandwidth and damping ratio.
Abstract: Iterative learning control (ILC) has been shown to be effective in improving tracking performance of repetitive tasks, and is widely used in the motion control systems of CNC machines, semiconductor manufacturing equipment, hard disk drives, etc. However, applying ILC to robot manipulators requires careful consideration of nonlinear dynamics. We propose using a computed torque controller and the disturbance observer (DOB) to robustly linearize the dynamics of robot manipulators. The PD feedback controller is then applied for each joint to achieve the desired bandwidth and damping ratio. Both control-based ILC and command-based ILC are implemented separately in the linearized system as a feedforward compensator to enhance trajectory tracking accuracy. The proposed control system is realized in a six-axis industrial robot. Experimental results show that DOB is indispensable for robust feedback linearization so that ILC can work on the linearized system to improve the tracking performance for repetitive motion. Satisfactory and similar performance is accomplished by both control-based ILC and command-based ILC.

27 citations


Cited by
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Journal ArticleDOI
TL;DR: The developed DPT scheme can be seamlessly integrated with the industrial robot controller and improve the robot's accuracy without retrofitting with high-end encoder and improving the tracking accuracy with eye-to-hand photogrammetry measurement feedback.
Abstract: In this paper, a practical dynamic path tracking (DPT) scheme for industrial robots is presented. The DPT scheme is a position-based visual servoing to realize three-dimensional dynamic path tracking by correcting the robot movement in real time. In the traditional task-implementation mode for industrial robots, the task planning and implementation are taught manually and hence the task accuracy largely depends on the repeatability of industrial robots. The proposed DPT scheme can realize automatic preplanned task and improve the tracking accuracy with eye-to-hand photogrammetry measurement feedback. Moreover, an adaptive Kalman filter is proposed to obtain smooth pose estimation and reduce the influence caused by image noise, vibration, and other uncertain disturbances. Due to high repeatability of the photogrammetry sensor, the proposed DPT scheme can achieve a high path tracking accuracy. The developed DPT scheme can be seamlessly integrated with the industrial robot controller and improve the robot's accuracy without retrofitting with high-end encoder. By using C-track 780 from Creaform as the photogrammetry sensor, the experimental tests on Fanuc M20-iA with the developed DPT scheme demonstrate the tracking accuracy is significantly improved ( $\pm 0.20 \text{ mm}$ for position and $\pm 0.10\text{ deg}$ for orientation).

58 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a systematic literature review on what enabling technologies can promote new circular business models and show that the realization of the circular economy involved two main changes: (i) managerial changes and (ii) legislative changes.
Abstract: Smart manufacturing is considered as a new paradigm that makes work smarter and more connected, bringing speed and flexibility through the introduction of digital innovation. Today, digital innovation is closely linked to the “sustainability” of companies. Digital innovation and sustainability are two inseparable principles that are based on the concept of circular economy. Digital innovation enables a circular economy model, promoting the use of solutions like digital platforms, smart devices, and artificial intelligence that help to optimize resources. Thus, the purpose of the research is to present a systematic literature review on what enabling technologies can promote new circular business models. A total of 31 articles were included in the study. Our results showed that realization of the circular economy involved two main changes: (i) managerial changes and (ii) legislative changes. Furthermore, the creation of the circular economy can certainly be facilitated by innovation, especially through the introduction of new technologies and through the introduction of digital innovations.

45 citations

Journal ArticleDOI
TL;DR: The developed dynamic pose correction scheme can make the industrial robots meet higher accuracy requirement in the applications such as riveting, drilling, and spot welding.
Abstract: In this article, a dynamic pose correction scheme is proposed to enhance the pose accuracy of industrial robots. The dynamic pose correction scheme uses the dynamic pose measurements as feedback to...

39 citations

Journal ArticleDOI
TL;DR: A Bayesian optimization algorithm is proposed to tune both the low-level controller parameters (i.e., the equivalent link-masses of the feedback linearizator and the feedforward controller) and the high-level controllers parameters, optimizing control parameters based on the specific trajectory to be executed.

32 citations

Journal ArticleDOI
06 Nov 2020-Sensors
TL;DR: Benefitting from the optical tracking system, the proposed procedure can be easily automated to improve the robot accuracy for applications requiring high positioning accuracy such as riveting, drill, and precise assembly.
Abstract: Robot positioning accuracy plays an important role in industrial automation applications. In this paper, a method is proposed for the improvement of robot accuracy with an optical tracking system that integrates a least-square numerical algorithm for the identification of kinematic parameters. In the process of establishing the system kinematics model, the positioning errors of the tool and the robot base, and the errors of the Denavit-Hartenberg parameters are all considered. In addition, the linear dependence among the parameters is analyzed. Numerical simulation based on a 6-axis UR robot is performed to validate the effectiveness of the proposed method. Then, the method is implemented on the actual robot, and the experimental results show that the robots can reach desired poses with an accuracy of ±0.35 mm for position and ±0.07° for orientation. Benefitting from the optical tracking system, the proposed procedure can be easily automated to improve the robot accuracy for applications requiring high positioning accuracy such as riveting, drill, and precise assembly.

13 citations