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鲁棒跟踪控制的微型机床负荷不确定性
为大家介绍一篇关于机床制造的外文，翻译摘要，说明出处及参考文献，希望对业内同行有所帮助，另如果需要更多资讯,请登录成海万能铣床http://www.chjc.cn.
中南大学学报
一月2012，19卷，问题1，PP 117-127
摘要
微机械加工结果的质量取决于显着的微型直线电机驱动的精密工作台的跟踪性能。直接驱动的设计的跟踪行为倾向等不确定性模型的参数变化和扰动。这种质量和阻尼比的不确定性进行了精密级鲁棒最优跟踪控制器的设计。质量和阻尼比的不确定性建模为结构性的参数不确定性模型。一种识别方法获得的参数不确定性是由使用无偏最小二乘法。外部干扰信号的瞬时频率带宽利用短时傅立叶变换技术分析。一二环路的跟踪控制策略相结合的?和扰动观测器（DOB）技术合成了。该?合成技术被用来设计鲁棒最优控制器基于结构化的不确定性模型。通过补充?控制器，DOB施加进一步提高抗干扰性能。为了评估所提出的控制策略的定位性能，比较实验进行了一个原型微铣床四台控制方案中：提出了两个环路的跟踪控制，单回路?控制，PID控制和PID控制的出生日期。干扰抑制性能，均方根（RMS）的跟踪误差和不同的控制方案的性能鲁棒性进行了研究。结果表明，该控制方案具有最好的定位性能。它减少了干扰力如60%和63.4%的均方根误差摩擦力与PID控制相比，最大误差引起的。PID控制相比，出生日期，它降低了均方根误差29.6%立式铣床http://www.x5032.com。
CHAE J, PARK S S, FREIHEIT T. Investigation of micro-cutting operations [J]. International Journal of Machine Tools & Manufacture, 2006, 46: 313–332. CrossRef
HUO De-hong, CHENG Kai, WARDLE F. 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. CrossRef
AFAZOV S M, RATCHEV S M, SEGAL J. Modelling and simulation of micro-milling cutting forces [J]. Journal of Materials Processing Technology, 2010, 210: 2154–2163. CrossRef
XU L, YAO Bin. 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. CrossRef立式铣床http://www.tzchenghai.com
LU Lu, YAO Bin, WANG Qing-feng, CHEN Zheng. Adaptive robust control of linear motors with dynamic friction compensation using modified LuGre model [J]. Automatica, 2009, 45: 2890–2896. CrossRef
MAKKAR C, HU G, SAWYER W G, DIXON W E. Lyapunov-based tracking control in the presence of uncertain nonlinear parameterizable friction [J]. IEEE Transactions on Automatic Control, 2007, 52(10): 1994–1998. CrossRef
HASANIEN H M, MUYEEN S M, TAMURA J. 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.
NASO D, CUPERTINO F, TURCHIANO B. Precise position control of tubular linear motors with neural networks and composite learning [J]. Control Engineering Practice, 2010, 18: 515–522. CrossRef
ALTER D M, TSAO T C. Stability of turning processes with actively controlled linear motorfeed drives [J]. ASME Journal of Engineering for Industry-Transactions, 1994, 116: 298–307. CrossRef万能铣床http://www.x52k.com
ALTER D M, TSAO T 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. CrossRef
为大家介绍一篇关于机床制造的外文，翻译摘要，说明出处及参考文献，希望对业内同行有所帮助，另如果需要更多资讯,请登录成海万能铣床http://www.chjc.cn.
中南大学学报
一月2012，19卷，问题1，PP 117-127
摘要
微机械加工结果的质量取决于显着的微型直线电机驱动的精密工作台的跟踪性能。直接驱动的设计的跟踪行为倾向等不确定性模型的参数变化和扰动。这种质量和阻尼比的不确定性进行了精密级鲁棒最优跟踪控制器的设计。质量和阻尼比的不确定性建模为结构性的参数不确定性模型。一种识别方法获得的参数不确定性是由使用无偏最小二乘法。外部干扰信号的瞬时频率带宽利用短时傅立叶变换技术分析。一二环路的跟踪控制策略相结合的?和扰动观测器（DOB）技术合成了。该?合成技术被用来设计鲁棒最优控制器基于结构化的不确定性模型。通过补充?控制器，DOB施加进一步提高抗干扰性能。为了评估所提出的控制策略的定位性能，比较实验进行了一个原型微铣床四台控制方案中：提出了两个环路的跟踪控制，单回路?控制，PID控制和PID控制的出生日期。干扰抑制性能，均方根（RMS）的跟踪误差和不同的控制方案的性能鲁棒性进行了研究。结果表明，该控制方案具有最好的定位性能。它减少了干扰力如60%和63.4%的均方根误差摩擦力与PID控制相比，最大误差引起的。PID控制相比，出生日期，它降低了均方根误差29.6%立式铣床http://www.x5032.com。
CHAE J, PARK S S, FREIHEIT T. Investigation of micro-cutting operations [J]. International Journal of Machine Tools & Manufacture, 2006, 46: 313–332. CrossRef
HUO De-hong, CHENG Kai, WARDLE F. 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. CrossRef
AFAZOV S M, RATCHEV S M, SEGAL J. Modelling and simulation of micro-milling cutting forces [J]. Journal of Materials Processing Technology, 2010, 210: 2154–2163. CrossRef
XU L, YAO Bin. 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. CrossRef立式铣床http://www.tzchenghai.com
LU Lu, YAO Bin, WANG Qing-feng, CHEN Zheng. Adaptive robust control of linear motors with dynamic friction compensation using modified LuGre model [J]. Automatica, 2009, 45: 2890–2896. CrossRef
MAKKAR C, HU G, SAWYER W G, DIXON W E. Lyapunov-based tracking control in the presence of uncertain nonlinear parameterizable friction [J]. IEEE Transactions on Automatic Control, 2007, 52(10): 1994–1998. CrossRef
HASANIEN H M, MUYEEN S M, TAMURA J. 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.
NASO D, CUPERTINO F, TURCHIANO B. Precise position control of tubular linear motors with neural networks and composite learning [J]. Control Engineering Practice, 2010, 18: 515–522. CrossRef
ALTER D M, TSAO T C. Stability of turning processes with actively controlled linear motorfeed drives [J]. ASME Journal of Engineering for Industry-Transactions, 1994, 116: 298–307. CrossRef万能铣床http://www.x52k.com
ALTER D M, TSAO T 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. CrossRef
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