Abstract
This paper proposes a multi-input multi-output (MIMO) disturbance feedforward controller to improve the rejection of floor vibrations in active vibration isolation systems for high-precision machinery. To minimize loss of performance due to model uncertainties, the feedforward controller is implemented as a self-tuning generalized FIR filter. This filter contains a priori knowledge of the poles, such that relatively few parameters have to be estimated which makes the algorithm computationally efficient. The zeros of the filter are estimated using the filtered-error least mean squares (FeLMS) algorithm. Residual noise shaping is used to reduce bias. Conditions on convergence speed, stability, bias, and the effects of sensor noise on the self-tuning algorithm are discussed in detail. The combined control strategy is validated on a 6-DOF Stewart platform, which serves as a multi-axis and hard-mounted vibration isolation system, and shows significant improvement in the rejection of floor vibrations.
| Original language | English |
|---|---|
| Pages (from-to) | 90-103 |
| Number of pages | 14 |
| Journal | Control Engineering Practice |
| Volume | 72 |
| DOIs | |
| Publication status | Published - 1 Mar 2018 |
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Keywords
- Active vibration isolation
- High-precision mechatronics
- Least mean squares optimization
- MIMO feedforward control
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Self-tuning MIMO disturbance feedforward control for active hard-mounted vibration isolators. / Beijen, M.A.; Heertjes, M.F.; van Dijk, J.W.; Hakvoort, W.B.J.
In: Control Engineering Practice, Vol. 72, 01.03.2018, p. 90-103.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Self-tuning MIMO disturbance feedforward control for active hard-mounted vibration isolators
AU - Beijen, M.A.
AU - Heertjes, M.F.
AU - van Dijk, J.W.
AU - Hakvoort, W.B.J.
PY - 2018/3/1
Y1 - 2018/3/1
N2 - This paper proposes a multi-input multi-output (MIMO) disturbance feedforward controller to improve the rejection of floor vibrations in active vibration isolation systems for high-precision machinery. To minimize loss of performance due to model uncertainties, the feedforward controller is implemented as a self-tuning generalized FIR filter. This filter contains a priori knowledge of the poles, such that relatively few parameters have to be estimated which makes the algorithm computationally efficient. The zeros of the filter are estimated using the filtered-error least mean squares (FeLMS) algorithm. Residual noise shaping is used to reduce bias. Conditions on convergence speed, stability, bias, and the effects of sensor noise on the self-tuning algorithm are discussed in detail. The combined control strategy is validated on a 6-DOF Stewart platform, which serves as a multi-axis and hard-mounted vibration isolation system, and shows significant improvement in the rejection of floor vibrations.
AB - This paper proposes a multi-input multi-output (MIMO) disturbance feedforward controller to improve the rejection of floor vibrations in active vibration isolation systems for high-precision machinery. To minimize loss of performance due to model uncertainties, the feedforward controller is implemented as a self-tuning generalized FIR filter. This filter contains a priori knowledge of the poles, such that relatively few parameters have to be estimated which makes the algorithm computationally efficient. The zeros of the filter are estimated using the filtered-error least mean squares (FeLMS) algorithm. Residual noise shaping is used to reduce bias. Conditions on convergence speed, stability, bias, and the effects of sensor noise on the self-tuning algorithm are discussed in detail. The combined control strategy is validated on a 6-DOF Stewart platform, which serves as a multi-axis and hard-mounted vibration isolation system, and shows significant improvement in the rejection of floor vibrations.
KW - Active vibration isolation
KW - High-precision mechatronics
KW - Least mean squares optimization
KW - MIMO feedforward control
UR - http://www.scopus.com/inward/record.url?scp=85037814647&partnerID=8YFLogxK
U2 - 10.1016/j.conengprac.2017.11.008
DO - 10.1016/j.conengprac.2017.11.008
M3 - Article
AN - SCOPUS:85037814647
VL - 72
SP - 90
EP - 103
JO - Control Engineering Practice
JF - Control Engineering Practice
SN - 0967-0661
ER -