2017
DOI: 10.1109/access.2017.2650959
|View full text |Cite
|
Sign up to set email alerts
|

Optimizing Adjustable Parameters of Servo Controller by Using UniNeuro-HUDGA for Laser-Auto-Focus-Based Tracking System

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
2
0

Year Published

2018
2018
2023
2023

Publication Types

Select...
6

Relationship

0
6

Authors

Journals

citations
Cited by 7 publications
(2 citation statements)
references
References 28 publications
0
2
0
Order By: Relevance
“…The material contains a lot of metallic compounds and hard spots, which are likely to induce cutting tool fracture, hard to guarantee the size and accuracy requirements [9]. Muammer et al [10] used ceramic tool and carbide cutter to turn Inconel-718 alloy, and indicated that the carbide cutter was better than ceramic tool for cutting Inconel-718 alloy. According to the comparison of different cutting speeds, the ceramic tool was applicable to high-speed machining, the carbide cutter was applicable to low-speed machining, and the cutting force was inversely proportional to cutting speed.…”
Section: Introductionmentioning
confidence: 99%
“…The material contains a lot of metallic compounds and hard spots, which are likely to induce cutting tool fracture, hard to guarantee the size and accuracy requirements [9]. Muammer et al [10] used ceramic tool and carbide cutter to turn Inconel-718 alloy, and indicated that the carbide cutter was better than ceramic tool for cutting Inconel-718 alloy. According to the comparison of different cutting speeds, the ceramic tool was applicable to high-speed machining, the carbide cutter was applicable to low-speed machining, and the cutting force was inversely proportional to cutting speed.…”
Section: Introductionmentioning
confidence: 99%
“…Back propagation (BP) network is widely used in temperature control for its simple structure and noise inhibiting ability (Treesatayapun, 2018); however, it still suffers from the probability of falling into local minimum points, which may slow network training speed, and thus, cannot be utilized for real-time system control. Similarly, as a model-based control strategy, adaptive control largely depends upon the accuracy of model identification, and it could not be utilized for multi-variable systems with time-varying parameters (Liu et al, 2017; Morosan et al, 2010).…”
Section: Introductionmentioning
confidence: 99%