The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
High-performance robust motion control of machine tools: an adaptive robust control approach and comparative experiments
Abstract
This paper studies the high-performance robust motion control of machine tools. The newly proposed adaptive robust control (ARC) is applied to make the resulting closed-loop system robust to model uncertainties, instead of the disturbance observer (DOB) design previously tested by many researchers. Compared to DOB, the proposed ARC has a better tracking performance and transient in the presence of discontinuous disturbances, such as Coulomb friction, and it is of a lower order. As a result, time-consuming and costly rigorous friction identification and compensation is alleviated, and overall tracking performance is improved. The ARC design can also handle large parameter variations and is flexible in introducing extra nonlinear robust control terms and parameter adaptations to further improve the transient response and tracking performance. An anti-integration windup mechanism is inherently built in the ARC and, thus, the problem of control saturation is alleviated. Extensive comparative experimental tests are performed, and the results show the improved performance of the proposed ARC.
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Cites
Slotine, J.-J. E., & Li, W. (1991) · CERN Document Server (European Organization for Nuclear Research) · Cited by 18,975
Nonlinear and adaptive control design
Krstić, M., Kokotović, P. V., & Kanellakopoulos, I. (1995) · Cited by 10,421
Sliding Modes in Control and Optimization
Utkin, V. I. (1992) · Springer eBooks · doi:10.1007/978-3-642-84379-2 · Cited by 6,684
Motion control for advanced mechatronics
Ohnishi, K., Shibata, M., & Murakami, T. (1996) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/3516.491410 · Cited by 1,878
Adaptive manipulator control: A case study
Slotine, J.-J. E., & Weiping, L. (1988) · IEEE Transactions on Automatic Control · doi:10.1109/9.14411 · Cited by 1,032
Adaptive robust control of SISO nonlinear systems in a semi-strict feedback form
Yao, B., & Tomizuka, M. (1997) · Automatica · doi:10.1016/s0005-1098(96)00222-1 · Cited by 724
Self-citationRobust speed control of DC servomotors using modern two degrees-of-freedom controller design
Umeno, T., & Hori, Y. (1991) · IEEE Transactions on Industrial Electronics · doi:10.1109/41.97556 · Cited by 723
Robust motion controller design for high-accuracy positioning systems
Lee, H. S., & Tomizuka, M. (1996) · IEEE Transactions on Industrial Electronics · doi:10.1109/41.481407 · Cited by 436
Self-citationSmooth Robust Adaptive Sliding Mode Control of Manipulators With Guaranteed Transient Performance
Yao, B., & Tomizuka, M. (1996) · Journal of Dynamic Systems, Measurement, and Control · doi:10.1115/1.2802355 · Cited by 256
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BAI, Y., YAO, J., HU, J., & FENG, G. (2025) · Chinese Journal of Aeronautics · doi:10.1016/j.cja.2024.07.041 · Cited by 11
Wang, Y., Zhao, J., Ding, H., & Zhang, H. (2021) · Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science · doi:10.1177/0954406220978263 · Cited by 10
Fixed-time adaptive neural network compensation control for uncertain nonlinear systems
Ma, J., Yao, Z., Deng, W., & Yao, J. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.107563 · Cited by 11
Metadata
- Authors
- Yao, B., Al-Majed, M., & Tomizuka, M.
- Venue
- IEEE/ASME Transactions on Mechatronics
- Published
- 1997-06
- Volume
- 2
- Issue
- 2
- Pages
- 63-76
- ISSN
- 1083-4435 (ISSN-L)
- OpenAlex
- W2088288066
- Cited by
- 295
- References
- 9
- FWCI
- 16.47
- Type
- journal article
- Language
- en
- Open access
- closed
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