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| 论文编号: |
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| 第一作者所在部门: |
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| 中文论文题目: |
An Adaptive Takagi-Sugeno Fuzzy Model-Based Predictive Controller for Piezoelectric Actuators
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| 英文论文题目: |
An Adaptive Takagi-Sugeno Fuzzy Model-Based Predictive Controller for Piezoelectric Actuators
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| 论文题目英文: |
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| 作者: |
Cheng, Long
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| 论文出处: |
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| 刊物名称: |
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
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| 年: |
2017
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| 卷: |
64 |
| 期: |
4 |
| 页: |
3048-3058 |
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| 影响因子: |
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| 摘要: |
Piezoelectric actuators (PEAs) are widely used in the nanopositioning applications due to their high stiffness, fast response, and ultrahigh precision. However, PEAs inherently have the hysteresis nonlinearity which can dramatically degrade the tracking performance. This paper proposes an adaptive Takagi-Sugeno (T-S) fuzzy model-based predictive controller with a parallel distributed control structure. Compared to the previous results, the proposed controller does not require the inverse hysteresis model of PEAs, and is easy to be calculated because the predictive subcontroller for each T-S fuzzy rule has an explicit form. Meanwhile, the parameters in the T-S fuzzy model can be online adjusted according to the real-time tracking error feedback, and the offline training accuracy of the T-S fuzzy model is no longer a serious concern. In addition, some physical constraints of the proposed controller can be well handled. To verify the proposed method, experiments are conducted on a commercial PEA product, and experiment results show that the proposed method has a satisfactory tracking performance. Furthermore, comparisons with some existing controllers are made and the proposed adaptive fuzzy model-based predictive controller outperforms these controllers. |
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