Adaptive feedforward compensation algorithms for active vibration control with mechanical coupling

Landau, Ioan Doré; Alma, Marouane; Airimiţoaie, Tudor-Bogdan

doi:10.1016/j.automatica.2011.08.015

Cited by 54 publications

(93 citation statements)

References 15 publications

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“…This can result in a possibly unstable feedback loop from the reaction forces to the floor plate accelerometers. An extensive discussion about this topic is found in, e.g., [17]. However, for the setup considered in this paper, no stability problems occurred during the measurements.…”

Section: Actuator-floor Interactionmentioning

confidence: 99%

“…As a result, a more computationally efficient algorithm can be obtained in which the system can be accurately described with generally less parameters. Examples are found in [16,17], but these works use IIR filters with self-tuning poles which can lead to instability because the poles are not bounded to the open unit disk. An alternative is found in using IIR filters with fixed poles [18,19], also called generalized FIR filters [20].…”

Section: Introductionmentioning

confidence: 99%

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Self-tuning MIMO disturbance feedforward control for active hard-mounted vibration isolators

Beijen

Heertjes

Dijk

et al. 2018

Control Engineering Practice

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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.

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Section: Actuator-floor Interactionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Self-tuning MIMO disturbance feedforward control for active hard-mounted vibration isolators

Beijen

Heertjes

Dijk

et al. 2018

Control Engineering Practice

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“…(63)). Relaxation of the positive real condition by averaging arguments is discussed in [26] and by adding proportional adaptation in [27]. Filtering of the residual error can also be considered for satisfying the positive real condition, but this will modify the criterion which is minimized ( [27,28]).…”

Section: Ave2014mentioning

confidence: 99%

Adaptive active vibration isolation – A control perspective

Landau

Airimiţoaie

Silva

et al. 2015

MATEC Web of Conferences

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Abstract. In many classes of applications like active vibration control and active noise control, the disturbances can be characterized by their frequencies content and their location in a specific region in the frequency domain. The disturbances can be of narrow band type (simple or multiple) or of broad band type. A model can be associated to these disturbances. The knowledge of the disturbance model as well as of the compensator system is necessary for the design of an appropriate control system in order to attenuate (or to reject) their effect upon the system to be controlled. The attenuation of disturbances by feedback is limited by the Bode Integral and the "water bed" effect upon the output sensitivity function. In such situations, the feedback approach has to be complemented by a "feedforward disturbance compensation" requiring an additional transducer for getting information upon the disturbance. Unfortunately in most of the situations the disturbances are unknown and time-varying and therefore an adaptive approach should be considered. The generic term for adaptive attenuation of unknown and time-varying disturbances is "adaptive regulation" (known plant model, unknown and time-varying disturbance model).The paper will review a number of recent developments for adaptive feedback compensation of multiple unknown and timevarying narrow band disturbances and for adaptive feedforward compensation of broad band disturbances in the presence of the inherent internal positive feedback caused by the coupling between the compensator system and the measurement of the image of the disturbance. Some experimental results obtained on a relevant active vibration control system will illustrate the performance of the various algorithms presented.

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“…Several new algorithms for adaptive feed-forward compensation, taking into account the existence of an inherent internal positive feedback coupling, are applied to an active vibration control system (Landau et al, 2011). Based on the adaptive filtering theory, the adaptive feed-forward filtered-X least mean square algorithm (FXLMS) control algorithm was first used for noise control (Burgess, 1981;Kuo and Morgan, 1995;Widrow et al, 1975) and then extended to vibration control (Kim et al, 1999;Pu et al, 2014;Yan et al, 2012;Yang et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Experiments on resonant vibration suppression of a piezoelectric flexible clamped–clamped plate using filtered-U least mean square algorithm

Qiu

Zhang

et al. 2014

Journal of Intelligent Material Systems and Structures

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This article investigates the adaptive filtered-U least mean square feed-forward algorithm for active resonant vibration control of a clamped-clamped flexible piezoelectric plate structure under persistent harmonic excitation. Different from the widely used filtered-X least mean square algorithm based on the finite impulse response filter, the filtered-U least mean square algorithm uses the infinite impulse response filter. An infinite impulse response filter can be constituted simply by using two adaptive transversal filters. The filtered-U least mean square algorithm can model the system accurately with much fewer coefficients. Moreover, the filtered-U least mean square algorithm has better control performance and stability in the presence of vibration control feedback, owing to the inherent zero-pole structure of the infinite impulse response filter. In this investigation, the filtered-U least mean square algorithm is implemented only in experiments. Two experimental cases are carried out, including the reference signal extracted from the function signal generator and the lead zirconate titanate sensor. A proportional-derivative feedback control algorithm is also applied as a comparison. The experimental results demonstrate the feasibility and performance of the designed proportional-derivative controller and filtered-U least mean square controller.

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Adaptive feedforward compensation algorithms for active vibration control with mechanical coupling

Cited by 54 publications

References 15 publications

Self-tuning MIMO disturbance feedforward control for active hard-mounted vibration isolators

Self-tuning MIMO disturbance feedforward control for active hard-mounted vibration isolators

Adaptive active vibration isolation – A control perspective

Experiments on resonant vibration suppression of a piezoelectric flexible clamped–clamped plate using filtered-U least mean square algorithm

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