Robust tracking control for micro machine tools with load uncertainties

Shi-xun Fan , Da-peng Fan , Hua-jie Hong , Zhi-yong Zhang

Journal of Central South University ›› 2012, Vol. 19 ›› Issue (1) : 117 -127.

PDF
Journal of Central South University ›› 2012, Vol. 19 ›› Issue (1) : 117 -127. DOI: 10.1007/s11771-012-0980-y
Article

Robust tracking control for micro machine tools with load uncertainties

Author information +
History +
PDF

Abstract

The quality of the micro-mechanical machining outcome depends significantly on the tracking performance of the miniaturized linear motor drive precision stage. The tracking behavior of a direct drive design is prone to uncertainties such as model parameter variations and disturbances. Robust optimal tracking controller design for this kind of precision stages with mass and damping ratio uncertainties was researched. The mass and damping ratio uncertainties were modeled as the structured parametric uncertainty model. An identification method for obtaining the parametric uncertainties was developed by using unbiased least square technique. The instantaneous frequency bandwidth of the external disturbance signals was analyzed by using short time Fourier transform technique. A two loop tracking control strategy that combines the µ-synthesis and the disturbance observer (DOB) techniques was proposed. The µ-synthesis technique was used to design robust optimal controllers based on structured uncertainty models. By complementing the µ controller, the DOB was applied to further improving the disturbance rejection performance. To evaluate the positioning performance of the proposed control strategy, the comparative experiments were conducted on a prototype micro milling machine among four control schemes: the proposed two-loop tracking control, the single loop µ control, the PID control and the PID with DOB control. The disturbance rejection performances, the root mean square (RMS) tracking errors and the performance robustness of different control schemes were studied. The results reveal that the proposed control scheme has the best positioning performance. It reduces the maximal errors caused by disturbance forces such as friction force by 60% and the RMS errors by 63.4% compared with the PID control. Compared to PID with DOB control, it reduces the RMS errors by 29.6%.

Keywords

micro machine tools servos / parametric uncertainty model / instantaneous frequency / disturbance observer / µ-synthesis

Cite this article

Download citation ▾
Shi-xun Fan, Da-peng Fan, Hua-jie Hong, Zhi-yong Zhang. Robust tracking control for micro machine tools with load uncertainties. Journal of Central South University, 2012, 19(1): 117-127 DOI:10.1007/s11771-012-0980-y

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

ChaeJ., ParkS. S., FreiheitT.. Investigation of micro-cutting operations [J]. International Journal of Machine Tools & Manufacture, 2006, 46: 313-332

[2]

HuoD.-h., ChengK., WardleF.. A holistic integrated dynamic design and modelling approach applied to the development of ultraprecision micro-milling machines [J]. International Journal of Machine Tools & Manufacture, 2010, 50: 335-343

[3]

AfazovS. M., RatchevS. M., SegalJ.. Modelling and simulation of micro-milling cutting forces [J]. Journal of Materials Processing Technology, 2010, 210: 2154-2163

[4]

XuL., YaoBin.. Adaptive robust precision motion control of linear motorswith negligible electrical dynamics: Theory and experiments [J]. IEEE/ASME Transactions on Mechatronics, 2001, 6(4): 444-452

[5]

LuL., YaoB., WangQ.-f., ChenZheng.. Adaptive robust control of linear motors with dynamic friction compensation using modified LuGre model [J]. Automatica, 2009, 45: 2890-2896

[6]

MakkarC., HuG., SawyerW. G., DixonW. E.. Lyapunov-based tracking control in the presence of uncertain nonlinear parameterizable friction [J]. IEEE Transactions on Automatic Control, 2007, 52(10): 1994-1998

[7]

HasanienH. M., MuyeenS. M., TamuraJ.. Speed control of permanent magnet excitation transverse flux linear motor by using adaptive neuro-fuzzy controller [J]. Energy Conversion and Management, 2010, 51: 2672-2768

[8]

NasoD., CupertinoF., TurchianoB.. Precise position control of tubular linear motors with neural networks and composite learning [J]. Control Engineering Practice, 2010, 18: 515-522

[9]

AlterD. M., TsaoT. C.. Stability of turning processes with actively controlled linear motorfeed drives [J]. ASME Journal of Engineering for Industry-Transactions, 1994, 116: 298-307

[10]

AlterD. M., TsaoT. C.. Control of linear motors for machine tool feed drives: Design and implementation of H-infinity optimal feedback control [J]. ASME Journal of Dynamic Systems Measurement and Control, 1996, 118: 649-656

[11]

Van den BraembusscheP., SweversJ., van BrusselH.. Design and experimental validation of robust controllers for machine tool drives with linear motor [J]. Mechatronics, 2001, 11: 545-562

[12]

ChoiC., TsaoT.-Chin.. Control of linear motor machine tool feed drives for end milling: robust MIMO approach [J]. Mechatronics, 2005, 15: 1207-1224

[13]

ShenB.-H., TsaiM.-Ching.. Robust dynamic stiffness design of linear servomotor drives [J]. Control Engineering Practice, 2006, 14: 1325-1336

[14]

ZhengK., LeeA. H., BentsmanJ., KreinP. T.. High performance robust linear controller synthesis for an induction motor using a multi-obrective hybrid control strategy [J]. Nonlinear Analysis, 2006, 65: 2061-2081

[15]

YenP.-lang.. A two-loop robust controller for compensation of the variant friction force in an over-constrained parallel kinematic machine [J]. International Journal of Machine Tools & Manufacture, 2008, 48: 1354-1365

[16]

Azadi YazdiE., NagamuneR.. Multiple robust H-infinity controller design using the nonsmooth optimization method [J]. International Journal of Robust and Nonlinear Control, 2010, 20(11): 1197-1312

[17]

GuD. W., PetkovP. H., KonstantinovM. M.Robust control design with MATLAB [M], 2005, Lodon, Springer Press: 71-74

[18]

DoyleJ., FrancisB., TannenbaumA.Feedback control theory [M], 1992, New York, McMillam: 195-204

[19]

ErkorkmazK., AltintasY.. High speed CNC system design. Part II: modeling and identification of feed drives [J]. International Journal of Machine Tools & Manufacture, 2001, 41: 1487-1509

[20]

MartonL., LantosB.. Control of mechanical systems with Stribeck friction and backlash [J]. System & Control Letters, 2009, 58: 141-147

[21]

LeeH. S., TomizukaM.. Robust motion controller design for high-accuracy positioning systems [J]. IEEE Transactions on Industrial Electronics, 1996, 43: 48-55

AI Summary AI Mindmap
PDF

131

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/