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    Development of Control Algorithm for Tractor Semi-Active Cabin Suspension based on Sliding Mode Control

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๋†์—…์ƒ๋ช…๊ณผํ•™๋Œ€ํ•™ ๋ฐ”์ด์˜ค์‹œ์Šคํ…œ๊ณตํ•™๊ณผ, 2022.2. ๋ฐ•์˜์ค€.ํŠธ๋ž™ํ„ฐ๋Š” ๋ถˆ๊ท ์ผํ•œ ์ง€๋ฉด์„ ์ฃผํ–‰ํ•˜๋ฉฐ ๋ถ€ํ•˜๋ณ€๋™์ด ํฐ ๋†์ž‘์—…์— ์ฃผ๋กœ ์‚ฌ์šฉ๋œ๋‹ค. ์ด๋กœ ์ธํ•ด ๋ฐœ์ƒํ•˜๋Š” ํŠธ๋ž™ํ„ฐ์˜ ์Šน์ฐจ์ง„๋™์€ ์ž‘์—…์ž์˜ ๊ฑด๊ฐ•์— ์œ„ํ˜‘์ด ๋˜๊ณ  ์žˆ๋‹ค. ๋•Œ๋ฌธ์— ํŠธ๋ž™ํ„ฐ ์บ๋นˆ์˜ ์Šน์ฐจ์ง„๋™์„ ์ €๊ฐํ•  ์ˆ˜ ์žˆ๋Š” ์—ฌ๋Ÿฌ ๋ฐฉ์•ˆ๋“ค์ด ์ œ์•ˆ๋˜์—ˆ์œผ๋‚˜, ์•„์ง๋„ ๊ตญ์ œ์  ๊ธฐ์ค€๋Ÿ‰์„ ๋„˜๋Š” ์Šน์ฐจ์ง„๋™์ด ๋ฐœ์ƒํ•˜๊ณ  ์žˆ๋‹ค. ์Šน์ฐจ์ง„๋™์„ ํšจ๊ณผ์ ์œผ๋กœ ์ €๊ฐํ•˜๋Š” ๋ฐฉ์•ˆ์œผ๋กœ ์บ๋นˆ ํ˜„๊ฐ€์žฅ์น˜๊ฐ€ ์ฃผ๋ชฉ์„ ๋ฐ›๊ณ  ์žˆ๋‹ค. ์บ๋นˆ ํ˜„๊ฐ€์žฅ์น˜๋กœ ์‚ฌ์šฉ๋  ์ˆ˜ ์žˆ๋Š” ์ˆ˜๋™(passive), ๋ฐ˜๋Šฅ๋™(semi-active), ๋Šฅ๋™(active) ํ˜„๊ฐ€์žฅ์น˜ ์ค‘์—์„œ ๋™๋ ฅ ์†์‹ค์ด ์ ์œผ๋ฉด์„œ๋„ ์Šน์ฐจ์ง„๋™ ์ €๊ฐ ์„ฑ๋Šฅ์ด ๋›ฐ์–ด๋‚œ ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋“ค์ด ์ˆ˜ํ–‰๋˜์–ด ์™”๋‹ค. ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜๋ฅผ ์ œ์–ดํ•˜๊ธฐ ์œ„ํ•œ ์—ฐ๊ตฌ๋“ค์€ ์Šน์šฉ์ฐจ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์ฃผ๋กœ ์ง„ํ–‰๋˜์—ˆ๋‹ค. ์Šค์นด์ดํ›…(skyhook), ์ตœ์ ์ œ์–ด, ํผ์ง€ ๋กœ์ง, ์Šฌ๋ผ์ด๋”ฉ ๋ชจ๋“œ ์ œ์–ด ๋“ฑ์˜ ๋‹ค์–‘ํ•œ ์ œ์–ด ๊ธฐ๋ฒ•์„ ํ†ตํ•ด ํšจ๊ณผ์ ์œผ๋กœ ์Šน์šฉ์ฐจ์˜ ์Šน์ฐจ์ง„๋™์„ ์ €๊ฐํ•œ ์—ฐ๊ตฌ ์‚ฌ๋ก€๊ฐ€ ๋‹ค์ˆ˜ ์ˆ˜ํ–‰๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ˜„๊ฐ€์ƒ ์งˆ๋Ÿ‰์ด ํ˜„๊ฐ€ํ•˜ ์งˆ๋Ÿ‰๋ณด๋‹ค ํฐ ์Šน์šฉ์ฐจ๋Š” ์‹œ์Šคํ…œ ๊ตฌ์กฐ์ ์œผ๋กœ ํŠธ๋ž™ํ„ฐ์™€ ๋‹ค๋ฅด๊ธฐ ๋•Œ๋ฌธ์—, ํŠธ๋ž™ํ„ฐ ๊ตฌ์กฐ๋ฅผ ๊ณ ๋ คํ•œ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•œ ์‹ค์ •์ด๋‹ค. ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜๊ฐ€ ์žฅ์ฐฉ๋œ ํŠธ๋ž™ํ„ฐ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•œ ์—ฐ๊ตฌ๋Š” ์ตœ์ ์ œ์–ด ๊ธฐ๋ฒ•์„ ์ด์šฉํ•œ ์—ฐ๊ตฌ์— ๋จธ๋ฌผ๋Ÿฌ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ตœ์ ์ œ์–ด ๊ธฐ๋ฒ•์€ ํŠธ๋ž™ํ„ฐ์˜ ๋ณต์žกํ•œ ์‹œ์Šคํ…œ์„ ์ •ํ™•ํ•˜๊ฒŒ ๊ตฌํ˜„ํ•˜์ง€ ๋ชปํ•จ์œผ๋กœ ์ธํ•ด ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ์‹œ์Šคํ…œ ๋ชจ๋ธ์˜ ๋ถˆํ™•์‹ค์„ฑ๊ณผ ์ž‘์—… ํ™˜๊ฒฝ์ด ์™ธ๋ž€์— ๋…ธ์ถœ๋˜๊ธฐ ์‰ฌ์šด ํ™˜๊ฒฝ์ด๋ผ๋Š” ์  ๋•Œ๋ฌธ์— ์ œ์–ด ์„ฑ๋Šฅ์ด ์ €ํ•˜๋  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํŠธ๋ž™ํ„ฐ ๊ตฌ์กฐ๋ฅผ ๊ณ ๋ คํ•œ 1/2(half-car) ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ์„ ๊ฐœ๋ฐœํ•˜๊ณ  ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜์˜ ํŠน์„ฑ๊ณผ ๋น„๋ก€์ œ์–ด๋ฐธ๋ธŒ ์ „๋ฅ˜์˜ ๋™ํŠน์„ฑ์„ ๊ตฌํ˜„ํ•˜์—ฌ ๋ชจ๋ธ์˜ ์ •ํ™•๋„๋ฅผ ๋†’์˜€๋‹ค. ๊ฐœ๋ฐœ๋œ ๋™์—ญํ•™ ๋ชจ๋ธ์„ ๋Œ€์ƒ์œผ๋กœ ๊ฐ•์ธ ์ œ์–ด ๊ธฐ๋ฒ•์ธ ์Šฌ๋ผ์ด๋”ฉ ๋ชจ๋“œ ์ œ์–ด๋ฅผ ์ด์šฉํ•˜์—ฌ ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ฐœ๋ฐœํ•˜๊ณ  ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋ฅผ ๋น„๊ตํ•˜์—ฌ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์„ฑ๋Šฅ์„ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ์— ๋”ฐ๋ฅด๋ฉด ๊ณ ๋ฌด๋งˆ์šดํŠธ๋ฅผ ์žฅ์ฐฉํ•œ ํŠธ๋ž™ํ„ฐ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์บ๋นˆ ์ˆ˜์ง ๊ฐ€์†๋„๋ณด๋‹ค ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜๋ฅผ ์žฅ์ฐฉํ•œ ํŠธ๋ž™ํ„ฐ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์บ๋นˆ ์ˆ˜์ง ๊ฐ€์†๋„๊ฐ€ ์ž…๋ ฅ ๋…ธ๋ฉด ์กฐ๊ฑด์ด ๊ณ„๋‹จ ์ž…๋ ฅ์ธ ๊ฒฝ์šฐ 55% ๊ฐ์†Œํ•˜์˜€๊ณ , ISO8608 ๋…ธ๋ฉด ๋“ฑ๊ธ‰์ธ ๊ฒฝ์šฐ 41% ๊ฐ์†Œํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœ๋œ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์‹ค์‹œ๊ฐ„์„ฑ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ œ์–ด๊ธฐ๋ฅผ ๋Œ€์ƒ์œผ๋กœ Hardware-in-the-Loop ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ง„ํ–‰ํ•˜์˜€๊ณ  ๋…ธ๋ฉด ์กฐ๊ฑด๊ณผ ์ƒ๊ด€์—†์ด ์บ๋นˆ ์ˆ˜์ง ๊ฐ€์†๋„์—์„œ ํฐ ๋ณ€ํ™”๊ฐ€ ๋‚˜ํƒ€๋‚˜์ง€ ์•Š์•„ ์‹ค์‹œ๊ฐ„์„ฑ์„ ๋งŒ์กฑํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค.Tractors travel on uneven ground and are mainly used for agricultural work with large load fluctuations. The resulting ride vibration of the tractor poses a threat to the health of the worker. Therefore, several studies have been done to reduce the ride vibration of the tractor cabin, but there are still ride vibrations that exceed the international standard. Cabin suspension is drawing attention as a way to effectively reduce ride vibrations. Among passive, semi-active, and active suspensions that can be used as cabin suspension, studies have been conducted on semi-active suspension because of its low power loss and excellent ride vibration reduction performance. Studies to control semi-active suspension were mainly conducted on passenger cars. There are many research cases that effectively reduce ride vibration of passenger car through various control techniques such as skyhook, optimal control, fuzzy logic, and sliding mode control. However, since tractor is systematically different from passenger car of which sprung mass is greater than the unsprung mass, research considering the tractor structure is needed. Research on tractors equipped with semi-active suspension remains in research using optimal control techniques. However, the optimal control technique may deteriorate control performance due to the uncertainty of the system parameter that may arise from the failure to accurately measure the complex system of the tractor and the fact that the working environment which is easily exposed to disturbance. Therefore, in this study, a half-car tractor dynamic model considering a tractor structure was developed, and the accuracy of the model was improved by reflecting the dynamic characteristics of the semi-active suspension and the proportional control valve current. And a semi-active suspension control algorithm was developed and applied to the dynamic model, using sliding mode control which is one of the robust control technique. The performance of the control algorithm was evaluated by comparing the simulation results. According to the simulation results, it was confirmed that the vertical acceleration of the cabin in the tractor equipped with the semi-active suspension decreased by 55% when the input road condition was a step input and decreased by 41% when the ISO8608 road level. And Hardware-in-the-Loop simulation was conducted on controllers to verify the real-time property of the developed control algorithm.1. ์„œ ๋ก  1 2. ์—ฐ๊ตฌ ๋ชฉ์  5 3. ๋ฌธํ—Œ ์—ฐ๊ตฌ 6 3.1. ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ 6 3.2. ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜ 7 4. 1/2 ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ ๊ฐœ๋ฐœ 10 4.1. ํŠธ๋ž™ํ„ฐ ์ œ์› 11 4.2. ๊ณ ๋ฌด๋งˆ์šดํŠธ ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ ๊ฐœ๋ฐœ 12 4.3. ํ˜„๊ฐ€์žฅ์น˜ ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ ๊ฐœ๋ฐœ 21 4.3.1. ํ˜„๊ฐ€์žฅ์น˜ 1/2 ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ 21 4.3.2. ์ˆ˜๋™ ๋ฐ ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜ ํŠน์„ฑ 30 4.3.3. ๋น„๋ก€์ œ์–ด๋ฐธ๋ธŒ ๋ชจ๋ธ 33 4.3.4. ํ˜„๊ฐ€์žฅ์น˜ ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ ๊ฒ€์ฆ 36 5. ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ฐœ๋ฐœ 42 5.1. ๋น„๋ก€์ œ์–ด๋ฐธ๋ธŒ ์ „๋ฅ˜ ์ถ”์ข… ์•Œ๊ณ ๋ฆฌ์ฆ˜ 42 5.1.1. PI ์ œ์–ด๊ธฐ ์„ค๊ณ„ 42 5.1.2. ์™ธ๋ž€๊ด€์ธก๊ธฐ ์„ค๊ณ„ 43 5.1.3. ์™ธ๋ž€๊ด€์ธก๊ธฐ ๊ฐ•์ธ์„ฑ ํ‰๊ฐ€ 46 5.2. ์Šฌ๋ผ์ด๋”ฉ ๋ชจ๋“œ ์ œ์–ด ๊ธฐ๋ฐ˜ ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜ 48 6. ํŠธ๋ž™ํ„ฐ ์ œ์–ด ๋ชจ๋ธ ๋ฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ 54 6.1. ํŠธ๋ž™ํ„ฐ ์ œ์–ด ๋ชจ๋ธ 54 6.2. Model-in-the-Loop ์‹œ๋ฎฌ๋ ˆ์ด์…˜ 58 6.2.1. ์ฃผํŒŒ์ˆ˜ ์˜์—ญ ๋ถ„์„ 58 6.2.2. ์‹œ๊ฐ„ ์˜์—ญ ๋ถ„์„ 60 6.3. Hardware-in-the-Loop ์‹œ๋ฎฌ๋ ˆ์ด์…˜ 69 6.3.1. Hardware-in-the-Loop ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์‹œ์Šคํ…œ ๊ตฌ์ถ• 69 6.3.2. Hardware-in-the-Loop ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ 72 7. ๊ฒฐ๋ก  77 8. ์ฐธ๊ณ  ๋ฌธํ—Œ 79 9. ๋ถ€๋ก 85์„

    Actinobacillus actinomycetemcomitans์— ์˜ํ•œ ์กฐ๊ณจ์„ธํฌ์˜ ๊ณจํก์ˆ˜ ์œ ๋„์ธ์ž์˜ ์ƒ์„ฑ์ฆ๊ฐ€

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    Dept. of Dentistry/์„์‚ฌ[ํ•œ๊ธ€] ์น˜์ฃผ์—ผ์€ ์—ผ์ฆ์„ฑ ์งˆํ™˜์œผ๋กœ ์น˜์กฐ๊ณจ์˜ ํŒŒ๊ดด๊ฐ€ ์ค‘์š”ํ•œ ์ž„์ƒ์  ํŠน์ง•์ด๋‹ค. ์กฐ๊ณจ์„ธํฌ๋Š” ๊ณจํก์ˆ˜๋ฅผ ์œ ๋„ํ•˜๋Š” receptor activator of NF-ฮบB ligand (RANKL), macrophage inflammatory protein (MIP)-1, tumor necrosis factor (TNF)-, Interleukin (IL)-1ฮฒ ๋ฐ IL-6์™€ ๊ฐ™์€ cytokine์„ ์ƒ์„ฑํ•˜์—ฌ ํŒŒ๊ณจ ์„ธํฌ ํ˜•์„ฑ์— ์žˆ์–ด์„œ ์ค‘์š”ํ•˜๋‹ค. ์น˜์ฃผ์—ผ์˜ ์›์ธ๊ท ์ธ Actinobacillus actinomycetemcomitans์˜ ์ƒํ”ผ์„ธํฌ ๋ฐ ๋‚ดํ”ผ์„ธํฌ ๋ถ€์ฐฉ ์นจํˆฌ๋Šฅ์— ๋Œ€ํ•œ ๊ธฐ์ „์ด ์ผ๋ถ€ ๋ฐํ˜€์ ธ ์žˆ์œผ๋‚˜ ๋ณธ ์„ธ๊ท ์˜ ์กฐ๊ณจ์„ธํฌ ๋ถ€์ฐฉ/์นจํˆฌ๋Šฅ์— ๋Œ€ํ•ด์„œ๋Š” ์•Œ๋ ค์ ธ ์žˆ์ง€ ์•Š๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” A. actinomycetemcomitans์˜ ์กฐ๊ณจ์„ธํฌ ๋ถ€์ฐฉ/์นจํˆฌ๋Šฅ ๋ฐ ๋ณธ ์„ธ๊ท ์˜ ๋ถ€์ฐฉ/์นจํˆฌ์— ์˜ํ•œ ์กฐ๊ณจ์„ธํฌ์˜ ๊ณจํก์ˆ˜์œ ๋„๋Šฅ ๋ณ€ํ™”๋ฅผ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. A. actinomycetemcomitans๋Š” ์กฐ๊ณจ์„ธํฌ์— ๋ถ€์ฐฉํ•˜์˜€์œผ๋ฉฐ ์ผ๋ถ€ ์„ธ๊ท ์€ ์„ธํฌ ๋‚ด๋กœ ์นจํˆฌํ•˜์˜€๋‹ค. ์กฐ๊ณจ์„ธํฌ ํ‘œ๋ฉด์— ๋ถ€์ฐฉํ•œ ์„ธ๊ท ์˜ ์ˆ˜๋Š” ์นจํˆฌํ•œ ์„ธ๊ท ์˜ ์ˆ˜ ๋ณด๋‹ค ๋งŽ์•˜๋‹ค. A. actinomycetemcomitans์— ์˜ํ•˜์—ฌ ๊ฐ์—ผ๋œ ์กฐ๊ณจ์„ธํฌ์—์„œ RANKL, MIP-1, TNF-, IL-1 ฮฒ ๋ฐ IL-6 mRNA์˜ ๋ฐœํ˜„์ด ์ฆ๊ฐ€ํ•˜์˜€๋‹ค. ์—ด์ฒ˜๋ฆฌ ์„ธ๊ท ์œผ๋กœ ์ฒ˜๋ฆฌํ•œ ์กฐ๊ณจ์„ธํฌ์—์„œ๋„ RANKL, MIP-1, TNF-, IL-1 ฮฒ ๋ฐ IL-6์˜ ๋ฐœํ˜„์ด ์ฆ๊ฐ€ํ•˜์˜€์œผ๋‚˜ ์ƒ๊ท ์— ์˜ํ•˜์—ฌ ๊ฐ์—ผ๋œ ๊ฒฝ์šฐ ์—ด์ฒ˜๋ฆฌ์„ธ๊ท ์— ์˜ํ•œ ๊ฒฝ์šฐ ๋ณด๋‹ค RANKL, MIP-1 ๋ฐ IL-6 mRNA์ด ๋” ๊ฐ•ํ•˜๊ฒŒ ๋ฐœํ˜„๋˜์—ˆ๋‹ค. ์ด๋“ค ๊ฒฐ๊ณผ๋Š” A. actinomycetemcomitans๊ฐ€ ์กฐ๊ณจ์„ธํฌ์— ๋ถ€์ฐฉ ๋ฐ ์นจํˆฌ๋ฅผ ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ A. actinomycetemcomitans์— ์˜ํ•œ ์กฐ๊ณจ์„ธํฌ ๊ฐ์—ผ์ด ์กฐ๊ณจ์„ธํฌ์˜ RANKL, MIP-1 ๋ฐ IL-6์˜ ์ƒ์„ฑ์„ ์ฆ๊ฐ€์‹œ์ผœ ์น˜์ฃผ์—ผ์‹œ ์•ผ๊ธฐ๋˜๋Š” ๊ณจํก์ˆ˜์— ๊ด€์—ฌํ•  ์ˆ˜ ์žˆ์Œ์„ ์‹œ์‚ฌํ•œ๋‹ค. [์˜๋ฌธ]Periodontitis is an inflammatory disorder and alveolar bone destruction is one of important characteristics. Actinobacillus actinomycetemcomitans is one of oral pathogens that causes periodontal disease. Osteoblasts play an important role in bone resorption. It has been reported that A. actinomycetemcomitans is able to adhere to and invade oral epithelial cells. However, it is unclear whether A. actinomycetemcomitans adheres to and invades osteoblasts. In this study, we examined the ability of A. actinomycetemcomitans for adherence and or invasion to osteoblalsts and the effect of live or heat-killed A. actinomycetemcomitans on expression of bone resorption inducing factors such as receptor activator of NF-ฮบB ligand (RANKL), macrophage inflammatory protein (MIP)-1ฮฑ, tumor necrosis factor (TNF)-, Interleukin (IL)-1ฮฒ, and IL-6. A. actinomycetemcomitans was able to adhere to and invade osteoblasts. The number of bacteria that adhered to osteoblasts is much higher than that of bacteria that invaded. In osteoblast Infected with live or heat-inactivated A. actinomycetemcomitans, mRNA level of RANKL, MIP-1ฮฑ, TNF-ฮฑ, IL-1ฮฒ, and IL-6 was higher than that in non-treated osteoblasts. The osteoblasts infected with live A. actinomycetemcomitans expressed more mRNA of RANKL, MIP-1ฮฑ, and IL-6 than those with the heat-inactivated A. actinomycetemcomitans. The induction level of TNF-ฮฑ and IL-1ฮฒ mRNA was similar in both cultures treated with live and heat-inactivated bacteria. These findings suggest that A. actinomycetemcomitans can adhere to and invade osteoblasts and that the infection of A. actinomycetemcomitans in osteoblasts increases expression of bone resorption inducing factors such as RANKL, MIP-1ฮฑ, and IL-6. These process may be involved in the increased osteoclastogenesis finally leads to bone resorption.ope

    DEEP LEARNING BASED TRAFFIC SIGNAL CONTROL METHOD AND DEVICE FOR RLR DETECTION AND ACCIDENT PREVENTION

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    ์ผ ์‹ค์‹œ์˜ˆ์— ๋”ฐ๋ฅธ ๊ตํ†ต ์‹ ํ˜ธ ์ œ์–ด ๋ฐฉ๋ฒ•์€ ๋ฏธ๋ฆฌ ์ •ํ•ด์ง„ ์˜์—ญ์„ ํ†ต๊ณผํ•˜๋Š” ํ•˜๋‚˜ ์ด์ƒ์˜ ์ฐจ๋Ÿ‰์˜ ๋ฐ์ดํ„ฐ๋ฅผ ์ˆ˜์ง‘ํ•˜๋Š” ๋‹จ๊ณ„, ์ˆ˜์ง‘๋œ ๋ฐ์ดํ„ฐ๋ฅผ ๊ฐ€๊ณตํ•˜๋Š” ๋‹จ๊ณ„, ๊ฐ€๊ณต๋œ ๋ฐ์ดํ„ฐ๋ฅผ ๋ฏธ๋ฆฌ ํ•™์Šต๋œ ์ธ๊ณต ์‹ ๊ฒฝ๋ง์— ์ž…๋ ฅํ•˜์—ฌ, ์ฐจ๋Ÿ‰์˜ ์šด์ „ ํŒจํ„ด์„ ์˜ˆ์ธกํ•˜๋Š” ๋‹จ๊ณ„, ์šด์ „ ํŒจํ„ด์— ๊ธฐ์ดˆํ•˜์—ฌ, ์ฐจ๋Ÿ‰ ์ค‘ ์ ์ƒ‰ ์‹ ํ˜ธ์—์„œ ๊ต์ฐจ๋กœ๋ฅผ ํ†ต๊ณผํ•˜๋Š” ํ•˜๋‚˜ ์ด์ƒ์˜ ์ฐจ๋Ÿ‰(Red Light Runner; RLR)์˜ ๊ต์ฐจ๋กœ ํ†ต๊ณผ ์‹œ๊ฐ„์„ ์˜ˆ์ธกํ•˜๋Š” ๋‹จ๊ณ„, ์˜ˆ์ธก๋œ ๊ต์ฐจ๋กœ ํ†ต๊ณผ ์‹œ๊ฐ„์— ๊ธฐ์ดˆํ•˜์—ฌ, RLR์˜ ์•ˆ์ „ ์‹œ๊ฐ„์„ ๊ณ„์‚ฐํ•˜๋Š” ๋‹จ๊ณ„, ๋ฐ ์•ˆ์ „ ์‹œ๊ฐ„์— ๊ธฐ์ดˆํ•˜์—ฌ, ์ „์ฒด ์ ์ƒ‰ ์‹ ํ˜ธ ์ข…๋ฃŒ ์‹œ๊ฐ„์„ ์—ฐ์žฅํ•˜๋Š” ๋‹จ๊ณ„๋ฅผ ํฌํ•จํ•œ๋‹ค

    Development of Control Algorithm for Tractor Semi-Active Cabin Suspension based on Sliding Mode Control

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    ํŠธ๋ž™ํ„ฐ๋Š” ๋ถˆ๊ท ์ผํ•œ ์ง€๋ฉด์„ ์ฃผํ–‰ํ•˜๋ฉฐ ๋ถ€ํ•˜๋ณ€๋™์ด ํฐ ๋†์ž‘์—…์— ์ฃผ๋กœ ์‚ฌ์šฉ๋œ๋‹ค. ์ด๋กœ ์ธํ•ด ๋ฐœ์ƒํ•˜๋Š” ํŠธ๋ž™ํ„ฐ์˜ ์Šน์ฐจ์ง„๋™์€ ์ž‘์—…์ž์˜ ๊ฑด๊ฐ•์— ์œ„ํ˜‘์ด ๋˜๊ณ  ์žˆ๋‹ค. ๋•Œ๋ฌธ์— ํŠธ๋ž™ํ„ฐ ์บ๋นˆ์˜ ์Šน์ฐจ์ง„๋™์„ ์ €๊ฐํ•  ์ˆ˜ ์žˆ๋Š” ์—ฌ๋Ÿฌ ๋ฐฉ์•ˆ๋“ค์ด ์ œ์•ˆ๋˜์—ˆ์œผ๋‚˜, ์•„์ง๋„ ๊ตญ์ œ์  ๊ธฐ์ค€๋Ÿ‰์„ ๋„˜๋Š” ์Šน์ฐจ์ง„๋™์ด ๋ฐœ์ƒํ•˜๊ณ  ์žˆ๋‹ค. ์Šน์ฐจ์ง„๋™์„ ํšจ๊ณผ์ ์œผ๋กœ ์ €๊ฐํ•˜๋Š” ๋ฐฉ์•ˆ์œผ๋กœ ์บ๋นˆ ํ˜„๊ฐ€์žฅ์น˜๊ฐ€ ์ฃผ๋ชฉ์„ ๋ฐ›๊ณ  ์žˆ๋‹ค. ์บ๋นˆ ํ˜„๊ฐ€์žฅ์น˜๋กœ ์‚ฌ์šฉ๋  ์ˆ˜ ์žˆ๋Š” ์ˆ˜๋™(passive), ๋ฐ˜๋Šฅ๋™(semi-active), ๋Šฅ๋™(active) ํ˜„๊ฐ€์žฅ์น˜ ์ค‘์—์„œ ๋™๋ ฅ ์†์‹ค์ด ์ ์œผ๋ฉด์„œ๋„ ์Šน์ฐจ์ง„๋™ ์ €๊ฐ ์„ฑ๋Šฅ์ด ๋›ฐ์–ด๋‚œ ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋“ค์ด ์ˆ˜ํ–‰๋˜์–ด ์™”๋‹ค. ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜๋ฅผ ์ œ์–ดํ•˜๊ธฐ ์œ„ํ•œ ์—ฐ๊ตฌ๋“ค์€ ์Šน์šฉ์ฐจ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ์ฃผ๋กœ ์ง„ํ–‰๋˜์—ˆ๋‹ค. ์Šค์นด์ดํ›…(skyhook), ์ตœ์ ์ œ์–ด, ํผ์ง€ ๋กœ์ง, ์Šฌ๋ผ์ด๋”ฉ ๋ชจ๋“œ ์ œ์–ด ๋“ฑ์˜ ๋‹ค์–‘ํ•œ ์ œ์–ด ๊ธฐ๋ฒ•์„ ํ†ตํ•ด ํšจ๊ณผ์ ์œผ๋กœ ์Šน์šฉ์ฐจ์˜ ์Šน์ฐจ์ง„๋™์„ ์ €๊ฐํ•œ ์—ฐ๊ตฌ ์‚ฌ๋ก€๊ฐ€ ๋‹ค์ˆ˜ ์ˆ˜ํ–‰๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ˜„๊ฐ€์ƒ ์งˆ๋Ÿ‰์ด ํ˜„๊ฐ€ํ•˜ ์งˆ๋Ÿ‰๋ณด๋‹ค ํฐ ์Šน์šฉ์ฐจ๋Š” ์‹œ์Šคํ…œ ๊ตฌ์กฐ์ ์œผ๋กœ ํŠธ๋ž™ํ„ฐ์™€ ๋‹ค๋ฅด๊ธฐ ๋•Œ๋ฌธ์—, ํŠธ๋ž™ํ„ฐ ๊ตฌ์กฐ๋ฅผ ๊ณ ๋ คํ•œ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•œ ์‹ค์ •์ด๋‹ค. ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜๊ฐ€ ์žฅ์ฐฉ๋œ ํŠธ๋ž™ํ„ฐ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•œ ์—ฐ๊ตฌ๋Š” ์ตœ์ ์ œ์–ด ๊ธฐ๋ฒ•์„ ์ด์šฉํ•œ ์—ฐ๊ตฌ์— ๋จธ๋ฌผ๋Ÿฌ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ตœ์ ์ œ์–ด ๊ธฐ๋ฒ•์€ ํŠธ๋ž™ํ„ฐ์˜ ๋ณต์žกํ•œ ์‹œ์Šคํ…œ์„ ์ •ํ™•ํ•˜๊ฒŒ ๊ตฌํ˜„ํ•˜์ง€ ๋ชปํ•จ์œผ๋กœ ์ธํ•ด ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ์‹œ์Šคํ…œ ๋ชจ๋ธ์˜ ๋ถˆํ™•์‹ค์„ฑ๊ณผ ์ž‘์—… ํ™˜๊ฒฝ์ด ์™ธ๋ž€์— ๋…ธ์ถœ๋˜๊ธฐ ์‰ฌ์šด ํ™˜๊ฒฝ์ด๋ผ๋Š” ์  ๋•Œ๋ฌธ์— ์ œ์–ด ์„ฑ๋Šฅ์ด ์ €ํ•˜๋  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํŠธ๋ž™ํ„ฐ ๊ตฌ์กฐ๋ฅผ ๊ณ ๋ คํ•œ 1/2(half-car) ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ์„ ๊ฐœ๋ฐœํ•˜๊ณ  ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜์˜ ํŠน์„ฑ๊ณผ ๋น„๋ก€์ œ์–ด๋ฐธ๋ธŒ ์ „๋ฅ˜์˜ ๋™ํŠน์„ฑ์„ ๊ตฌํ˜„ํ•˜์—ฌ ๋ชจ๋ธ์˜ ์ •ํ™•๋„๋ฅผ ๋†’์˜€๋‹ค. ๊ฐœ๋ฐœ๋œ ๋™์—ญํ•™ ๋ชจ๋ธ์„ ๋Œ€์ƒ์œผ๋กœ ๊ฐ•์ธ ์ œ์–ด ๊ธฐ๋ฒ•์ธ ์Šฌ๋ผ์ด๋”ฉ ๋ชจ๋“œ ์ œ์–ด๋ฅผ ์ด์šฉํ•˜์—ฌ ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ฐœ๋ฐœํ•˜๊ณ  ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋ฅผ ๋น„๊ตํ•˜์—ฌ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์„ฑ๋Šฅ์„ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ์— ๋”ฐ๋ฅด๋ฉด ๊ณ ๋ฌด๋งˆ์šดํŠธ๋ฅผ ์žฅ์ฐฉํ•œ ํŠธ๋ž™ํ„ฐ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์บ๋นˆ ์ˆ˜์ง ๊ฐ€์†๋„๋ณด๋‹ค ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜๋ฅผ ์žฅ์ฐฉํ•œ ํŠธ๋ž™ํ„ฐ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์บ๋นˆ ์ˆ˜์ง ๊ฐ€์†๋„๊ฐ€ ์ž…๋ ฅ ๋…ธ๋ฉด ์กฐ๊ฑด์ด ๊ณ„๋‹จ ์ž…๋ ฅ์ธ ๊ฒฝ์šฐ 55% ๊ฐ์†Œํ•˜์˜€๊ณ , ISO8608 ๋…ธ๋ฉด ๋“ฑ๊ธ‰์ธ ๊ฒฝ์šฐ 41% ๊ฐ์†Œํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœ๋œ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์‹ค์‹œ๊ฐ„์„ฑ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ œ์–ด๊ธฐ๋ฅผ ๋Œ€์ƒ์œผ๋กœ Hardware-in-the-Loop ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ง„ํ–‰ํ•˜์˜€๊ณ  ๋…ธ๋ฉด ์กฐ๊ฑด๊ณผ ์ƒ๊ด€์—†์ด ์บ๋นˆ ์ˆ˜์ง ๊ฐ€์†๋„์—์„œ ํฐ ๋ณ€ํ™”๊ฐ€ ๋‚˜ํƒ€๋‚˜์ง€ ์•Š์•„ ์‹ค์‹œ๊ฐ„์„ฑ์„ ๋งŒ์กฑํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค.Tractors travel on uneven ground and are mainly used for agricultural work with large load fluctuations. The resulting ride vibration of the tractor poses a threat to the health of the worker. Therefore, several studies have been done to reduce the ride vibration of the tractor cabin, but there are still ride vibrations that exceed the international standard. Cabin suspension is drawing attention as a way to effectively reduce ride vibrations. Among passive, semi-active, and active suspensions that can be used as cabin suspension, studies have been conducted on semi-active suspension because of its low power loss and excellent ride vibration reduction performance. Studies to control semi-active suspension were mainly conducted on passenger cars. There are many research cases that effectively reduce ride vibration of passenger car through various control techniques such as skyhook, optimal control, fuzzy logic, and sliding mode control. However, since tractor is systematically different from passenger car of which sprung mass is greater than the unsprung mass, research considering the tractor structure is needed. Research on tractors equipped with semi-active suspension remains in research using optimal control techniques. However, the optimal control technique may deteriorate control performance due to the uncertainty of the system parameter that may arise from the failure to accurately measure the complex system of the tractor and the fact that the working environment which is easily exposed to disturbance. Therefore, in this study, a half-car tractor dynamic model considering a tractor structure was developed, and the accuracy of the model was improved by reflecting the dynamic characteristics of the semi-active suspension and the proportional control valve current. And a semi-active suspension control algorithm was developed and applied to the dynamic model, using sliding mode control which is one of the robust control technique. The performance of the control algorithm was evaluated by comparing the simulation results. According to the simulation results, it was confirmed that the vertical acceleration of the cabin in the tractor equipped with the semi-active suspension decreased by 55% when the input road condition was a step input and decreased by 41% when the ISO8608 road level. And Hardware-in-the-Loop simulation was conducted on controllers to verify the real-time property of the developed control algorithm.1. ์„œ ๋ก  1 2. ์—ฐ๊ตฌ ๋ชฉ์  5 3. ๋ฌธํ—Œ ์—ฐ๊ตฌ 6 3.1. ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ 6 3.2. ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜ 7 4. 1/2 ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ ๊ฐœ๋ฐœ 10 4.1. ํŠธ๋ž™ํ„ฐ ์ œ์› 11 4.2. ๊ณ ๋ฌด๋งˆ์šดํŠธ ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ ๊ฐœ๋ฐœ 12 4.3. ํ˜„๊ฐ€์žฅ์น˜ ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ ๊ฐœ๋ฐœ 21 4.3.1. ํ˜„๊ฐ€์žฅ์น˜ 1/2 ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ 21 4.3.2. ์ˆ˜๋™ ๋ฐ ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜ ํŠน์„ฑ 30 4.3.3. ๋น„๋ก€์ œ์–ด๋ฐธ๋ธŒ ๋ชจ๋ธ 33 4.3.4. ํ˜„๊ฐ€์žฅ์น˜ ํŠธ๋ž™ํ„ฐ ๋™์—ญํ•™ ๋ชจ๋ธ ๊ฒ€์ฆ 36 5. ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ฐœ๋ฐœ 42 5.1. ๋น„๋ก€์ œ์–ด๋ฐธ๋ธŒ ์ „๋ฅ˜ ์ถ”์ข… ์•Œ๊ณ ๋ฆฌ์ฆ˜ 42 5.1.1. PI ์ œ์–ด๊ธฐ ์„ค๊ณ„ 42 5.1.2. ์™ธ๋ž€๊ด€์ธก๊ธฐ ์„ค๊ณ„ 43 5.1.3. ์™ธ๋ž€๊ด€์ธก๊ธฐ ๊ฐ•์ธ์„ฑ ํ‰๊ฐ€ 46 5.2. ์Šฌ๋ผ์ด๋”ฉ ๋ชจ๋“œ ์ œ์–ด ๊ธฐ๋ฐ˜ ๋ฐ˜๋Šฅ๋™ ํ˜„๊ฐ€์žฅ์น˜ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜ 48 6. ํŠธ๋ž™ํ„ฐ ์ œ์–ด ๋ชจ๋ธ ๋ฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ 54 6.1. ํŠธ๋ž™ํ„ฐ ์ œ์–ด ๋ชจ๋ธ 54 6.2. Model-in-the-Loop ์‹œ๋ฎฌ๋ ˆ์ด์…˜ 58 6.2.1. ์ฃผํŒŒ์ˆ˜ ์˜์—ญ ๋ถ„์„ 58 6.2.2. ์‹œ๊ฐ„ ์˜์—ญ ๋ถ„์„ 60 6.3. Hardware-in-the-Loop ์‹œ๋ฎฌ๋ ˆ์ด์…˜ 69 6.3.1. Hardware-in-the-Loop ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์‹œ์Šคํ…œ ๊ตฌ์ถ• 69 6.3.2. Hardware-in-the-Loop ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ 72 7. ๊ฒฐ๋ก  77 8. ์ฐธ๊ณ  ๋ฌธํ—Œ 79 9. ๋ถ€๋ก 85์„

    METHOD FOR A PARALLELIZATION ALGORITHM FOR REAL-TIME PATH PLANNING OF HIGH-DOFs ROBOT MANIPULATOR AND DEVICE THEREOF

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    ๋ณธ ๊ฐœ์‹œ(disclosure)์˜ ๋‹ค์–‘ํ•œ ์‹ค์‹œ ์˜ˆ๋“ค์— ๋”ฐ๋ฅด๋ฉด, ๋™์ž‘ ๊ฒฝ๋กœ ๊ฐœ์„ ์„ ์œ„ํ•œ ๋งค๋‹ˆํ“ฐ๋ ˆ์ดํ„ฐ(manipulator) ์žฅ์น˜์˜ ๋™์ž‘ ๋ฐฉ๋ฒ•์€, ๊ธฐ์กด ๊ฒฝ๋กœ์—์„œ ๋ถ€๋ถ„ ๊ฒฝ๋กœ๋“ค์„ ๊ฒฐ์ •ํ•˜๋Š” ๊ณผ์ •๊ณผ, ์ƒ๊ธฐ ๋ถ€๋ถ„ ๊ฒฝ๋กœ๋“ค์˜ ๊ฐ๊ฐ์— ๋Œ€์‘ํ•˜๋Š” ๊ด€์ ˆ ์กฐํ•ฉ๋“ค์„ ๊ฒฐ์ •ํ•˜๋Š” ๊ณผ์ •๊ณผ, ์ƒ๊ธฐ ๊ด€์ ˆ ์กฐํ•ฉ๋“ค์— ๋Œ€ํ•ด ๊ฒฝ๋กœ ๊ฐœ์„ ์„ ์ˆ˜ํ–‰ํ•จ์œผ๋กœ์จ, ์ƒ๊ธฐ ๋ถ€๋ถ„ ๊ฒฝ๋กœ๋“ค์˜ ๊ฐ๊ฐ์— ๋Œ€์‘ํ•˜๋Š” ๊ฐœ์„ ๋œ ๋ถ€๋ถ„ ๊ฒฝ๋กœ๋“ค์„ ์ƒ์„ฑํ•˜๋Š” ๊ณผ์ •๊ณผ, ์ƒ๊ธฐ ๊ฐœ์„ ๋œ ๋ถ€๋ถ„ ๊ฒฝ๋กœ๋“ค ์ค‘์— ์ƒ๊ธฐ ๋ถ€๋ถ„ ๊ฒฝ๋กœ๋“ค์˜ ๊ฐ๊ฐ์— ๋Œ€์‘ํ•˜๋Š” ๊ฒฝ๋กœ ๊ฐœ์„  ํšจ๊ณผ๊ฐ€ ๊ฐ€์žฅ ํฐ ๋ถ€๋ถ„๊ฒฝ๋กœ๋“ค์„ ๊ฒฐ์ •ํ•˜๋Š” ๊ณผ์ •๊ณผ, ์ƒ๊ธฐ ๋ถ€๋ถ„ ๊ฒฝ๋กœ๋“ค์„ ๋Œ€์‘ํ•˜๋Š” ์ƒ๊ธฐ ๊ฒฝ๋กœ ๊ฐœ์„  ํšจ๊ณผ๊ฐ€ ๊ฐ€์žฅ ํฐ ๋ถ€๋ถ„ ๊ฒฝ๋กœ๋“ค๋กœ ๋ณ€๊ฒฝํ•˜๋Š” ๊ณผ์ •์„ ํฌํ•จํ•  ์ˆ˜ ์žˆ๋‹ค

    High Reliability Autonomous Driving System Architecture

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    ์ž์œจ ์ฃผํ–‰ ์ฐจ๋Ÿ‰์˜ ์ œ์–ด ๋ฐฉ๋ฒ• ๋ฐ ์žฅ์น˜๊ฐ€ ์ œ๊ณต๋œ๋‹ค. ์ž์œจ ์ฃผํ–‰ ์ฐจ๋Ÿ‰์˜ ์ฃผ๋ณ€์— ๋Œ€ํ•œ ์„ผ์‹ฑ ๋ฐ์ดํ„ฐ๋ฅผ ์ˆ˜์‹ ํ•˜์—ฌ, ์ž์œจ ์ฃผํ–‰ ์ฐจ๋Ÿ‰์˜ ์ฃผํ–‰ ํ™˜๊ฒฝ ์ธ์‹ ๋ฐ์ดํ„ฐ๋ฅผ ๊ฒฐ์ •ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ œ1 ๋ชจ๋“ˆ์—์„œ, ์„ผ์‹ฑ ๋ฐ์ดํ„ฐ์— ๊ธฐ์ดˆํ•˜์—ฌ ์ž์œจ ์ฃผํ–‰ ์ฐจ๋Ÿ‰์˜ ์ œ1 ์ฃผํ–‰ ๊ฒฝ๋กœ๋ฅผ ์˜ˆ์ธกํ•˜๊ณ , ์ œ2 ๋ชจ๋“ˆ์—์„œ, ์ฃผํ–‰ ํ™˜๊ฒฝ ์ธ์‹ ๋ฐ์ดํ„ฐ์— ๊ธฐ์ดˆํ•˜์—ฌ ์ž์œจ ์ฃผํ–‰ ์ฐจ๋Ÿ‰์˜ ์ œ2 ์ฃผํ–‰ ๊ฒฝ๋กœ๋ฅผ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋‹ค. ์ œ1 ์ฃผํ–‰ ๊ฒฝ๋กœ์™€ ์ œ2 ์ฃผํ–‰ ๊ฒฝ๋กœ๋ฅผ ๋น„๊ตํ•˜์—ฌ ์ตœ์ข… ์ฃผํ–‰ ๊ฒฝ๋กœ๋ฅผ ์„ ํƒํ•œ๋‹ค

    Drawbar Pull Estimation in Agricultural Tractor Tires on Asphalt Road Surface using Magic Formula

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    Agricultural tractors drive and operate both off-road and on-road. Tire road interaction significantly affects the โ€“tractive performance of a tractor, which is difficult to predict numerically. Many empirical models have beendeveloped to predict the tractive performance of tractors using the cone index, which can be measured throughsimple tests. However, a magic formula model that can determine the tractive performance without a cone indexcan be used instead of traditional empirical models as the cone index cannot be measured on asphalt roads. Theaim of this study was to predict the tractive performance of a tractor using the magic formula tire model. Thetraction force of the tires on an asphalt road was measured using an agricultural tractor. The dynamic wheelload was calculated to derive the coefficients of the traction slip curve using the measured static wheel load and โ€“drawbar pull of the tractor. Curve fitting was performed to fit the experimental data using the magic formula. The parameters of the magic formula tire model were well identified, and the model successfully determined thecoefficient of traction of the tractor.N
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