別紙4 (課程博士)
Dale of submlsslon

平成DepaHment

29年

7月

10日

StⅡden11D N11mber

機械工学専攻PP11Ca11t's na1ηe

氏名学t耒昔稲、号'弔 125120 号

SIMBAKENNETHRENNYSupervlsors

内山直樹

指導教員

柳田秀記

Abstract

論文内容の要旨(博士)Title ofThesis

博士学位論文名

Smooth Traject01'y Genel'ation and control for precision Motion of lndustrial MechatronicSystems(産業メカトロニクスシステムの精密弱]作のための滑らかな軌道生成と制笹わ(Approx.80o words)(要旨に00字程度)
The relnarkable techn010gical advancement in mechatronics, the synergetic application ofelectrical, electronic, computer, and control engineering, which has evolved over the past
three decades, has led to a novel staσe of life.1n response to the rapid growth oftechn010gy
and demand for precise products, the industrial community stiⅡ require hiσher・accuracy andhigher・speed manufacturing systems.1he precision of mechatronic systelns depends mostly
On the ability to overcome nonlinear uncertainties,、Nhich are common and generaⅡyUnavoidable. They result either from disturbance signals or systeln mode11ing errors.＼入lhen a
System is approximated by a mathematica11nodel, non‑fundamental factors are normaⅡyignored; for example, high・frequency dynamics and mechanical vibrations which are causedby the system itself
Ihe primary reasons for the existence of mechanical vibrations in mechatronic syslelns arehighly・dynamic lnotion trajectories in the drive systems and elasticities of mechanical
Systems due to lightweight elelnents, such as gears and lead screws. Highly・dynamic motion
trajectories contain a wide range of frequencies that can excite resonance n'equencies ofmechatronic system.1n machining complex parts or traversing con〕plex paths, reference
trajectorles lnay include hlgh curvatures that cause rapid changes in acceleration profiles.10
avoid this, the motion has to stop, change direction, and restart at eva'y corner. This type ofmotion proale causes discontinuity, consumes tilne and power, introduces delay, and brings
Unnecessary wear on mechatronic systems. For guaranteeing smootl〕 motion profiles,
reference trajectories should describe paths accurately and be kinematica11y smooth andSatisfy physica1 1ilnitations of mechatronic systems.1rajectories should also observe
important criteria depending on a specific application
Although many trajectory generation approaches have been discussed in the lita'ature, several
Problelns persist. For example, many studies in mobile robots considered only thefundamental criteria, such as traveHng distance and expected arrivaltime for generatingreference trajectories. other important criteria,1ike local contr0Ⅱability, such that anyChanges in the trajectory affect only its Hmited region, and arbitrarily setting ability of the丘rst and second derivatives of positions at the starting and endinσ Points of the path or patl〕
Segment are normaⅡy ignored. These two criteria aⅡ0、¥ smooth update of the trajectory andare ilnportant for obstacle avoidance motion planning t11rough which the trajectory has to be
re・planned lNhenever an obstacle is encountered.1n addition, for numerical control systelns,
many studies focus on smoothing linear interpolated to01・path points using a parametric
SPHne curve fitting technique. HO、Never, the curve fitting technique exl〕ibit osci11ations intrajectories with densely to01・path points

In addition to smooth motion profiles, mechatronic systelns require precise motion contr0Ⅱers
that achieve high tracking band、Nidth with disturbance rejections. High tracking band、Nidth
increases aexibility on tracking different trajectory profiles. Although traditional feedback
Contr011ers with high gains can achieve disturbance rejections, high gains may destabilise
Control systems and have severa11imitations due to hard、Nare properties. Because most ofindustrial mechatronic systems perform repetitlve operations over a fixed time interval,
Iterative Learning contr01(1LC) can be used as an effective tool for improving the transienl
response and tracking P引'formance. Although lLc has been widely applied into lnechatronicSystems, particularly feed drive systems,1nany studies consida'ed only tracking errors
However, tracking error・based contr011ers exhibit poorer tracking capability for contours 、Nlthhigh curvatures and show higher input variance than contouring contr011a'S. For tl〕is reason,1t
is indispensable t0 ム.1rther enhance systems pa'formance by considering contouring contr01
In order to enhance precision of the industnal mechatronic systelns, nlethods lo gena'ate
Slnooth trajectories and iterative learning conu'ol design for lnechatronic systemS 磁'edescribed in this thesis as f0ⅡOWS:1ntroductory remω'k is presented in chapt引' 1 f0Ⅱ0、¥ed bya revie、刃 ofrelated works and their shortc0111ings in chapter 2. chapter 3 Provides a lnethod togenerate smooth motion trajectories for autonolnous mobile robots for bolh real・tilne andOff、1ine applications.1he method is based on piecewise quintic B6Zier curves, where B6Ziel
Subdivision technique is adopted to improve curvatures at shω'p corners. The gen田'atedtrajectories are locaⅡy contr0Ⅱable and have arbitrarily setting ability ofthe first and second
derivatives at the starting and ending points. A method to generate vision・based slnootl)
Obstacle avoidance trajectories for mobile robots is presented in chapter 4.1he smooth anddistance・optimaltrajectory ls gena'ated in real・time from an environmentaltop・view image,
Where a fisl〕eye lens is used to capture a 、Nide area at low height. chapter 5 deplcts a lnethod
to generate smooth molion {rajectories for feed drive systems for a specified error tolerance ina reference contour. The generated trajectory considerS 会.1ndamental criteria,1.e., velocity,acceleration, and jerk lilnits.1his trajectory can be easily tracked by a feed drive systeln andrenders less lnaxilnum contour error as compared with conventionaltrajectories that are
Iinearly interpolated. A novelita'ative learning contouring contr0Ⅱ引' for feed drive systelns isPresented in chapter 6. Experimental results verined that with the proposed contr0Ⅱer, themaximum contour error in feed drive systems can be reduced by about 47.8% on the ava'age
as compared with conventional contr011ers. Lastly, chapter 7 describes concluding relnarks ofthis thesis and prospective future works