期刊
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
卷 146, 期 -, 页码 -出版社
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2020.106985
关键词
Active vibration control; Neural network decoupling; Inverse system; Adaptive feedforward control; Internal mode control
资金
- National Natural Science Foundation of China [51822502, 51475117]
- Foundation for Innovative Research Groups of the Natural Science Foundation of China [51521003]
- Fundamental Research Funds for the Central Universities [HIT.BRETIV.201903]
This article introduces a maglev vibration isolation platform (MVIP) aimed at attenuating vibration in payload-agnostic tasks under dynamic environments. By proposing a new control strategy, the article addresses coupling issues in payload-agnostic vibration control and offers unique and effective solutions.
Payload-specific vibration control may be suitable for a particular task but lacks generality and transferability required for adapting to the various payload. Self-decoupling and robust vibration control are the crucial problem to achieve payload-agnostic vibration control. However, there are problems still unsolved. In this article, we present a maglev vibration isolation platform (MVIP), which aims to attenuate vibration in payload-agnostic task under dynamic environment. Since efforts trying to suppress disturbance will encounter inevitable coupling problems, we analyzed the reasons resulting in it and proposed unique and effective solutions. To achieve payload-agnostic vibration control, we proposed a new control strategy, which is the main contribution of this article. It consists of self-construct radial basis function neural network inversion (SRBFNNI) decoupling scheme and hybrid adaptive feed-forward internal model control (HAFIMC). The former one enables the MVIP creating a self inverse model with little prior knowledge and achieving self-decoupling. For the unique structure of MVIP, the vibration control problem is stated and addressed by the proposed HAFIMC, which utilizes the adaptive part to deal with the periodical disturbance and the internal mode part to deal with the stability. (C) 2020 Elsevier Ltd. All rights reserved.
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