Magnetic resonance imaging in patients with meningitis induced hearing loss

The aim of this multicentre study was to compare T1 with T2 weighted MRI scans of the labyrinth after meningitis and to investigate whether waiting with scanning improved the reliability of diagnosing an ongoing process such as cochlear osteogenesis. Forty-five patients were included who suffered from meningitis induced hearing loss (radiological imaging <1 year after meningitis). Twenty-one gadolinium enhanced T1 and 45 T2 weighted MRI scans were scored by two radiologists regarding the condition of the labyrinth. These radiological observations were compared with the condition of the cochlea as described during cochlear implantation. A higher percentage of agreement with surgery was found for T2 (both radiologists 73%) than for T1 weighted MRI scans (radiologist 1: 62%, radiologist 2: 67%), but this difference is not significant. There was no significant difference between early (0–3 months) and late (>3 months) scanning, showing that radiological imaging soon after meningitis allows early diagnosis without suffering from a lower agreement with surgical findings

Two-sensor control in active vibration isolation using hard mounts

To isolate precision machines from floor vibrations, active vibration isolators are often applied. In this paper, a two-sensor control strategy, based on acceleration feedback and force feedback, is proposed for an active vibration isolator using a single-axis active hard mount. The hard mount provides a stiff support while an active control system is used to get the desired isolation performance. In our previous work, we showed that a sensor fusion control strategy for active hard mounts can be used to realize three performance objectives simultaneously: providing isolation from floor vibrations, achieving a low sensitivity for direct disturbance forces, and adding damping to internal modes of the supported precision machine. In the present work, an enhanced control strategy is presented, referred to as two-sensor control. We will show that two-sensor control outperforms sensor fusion, because it has more possibilities for loop-shaping and has better stability properties. The two-sensor control strategy is successfully validated on an experimental setu

Modeling and feedforward compensation of air mounts with internal Helmholtz resonances

This paper presents a disturbance feedforward control strategy for active vibration isolation systems with internal air mount dynamics. First, a parametric model of an air mount system including a Helmholtz resonance is derived, which is an extension to the widely used massless spring-damper models for vibration isolators. Second, a self-tuning feedforward controller is proposed that fine-tunes the parameters of the model online. This refers to zeros only because the poles of the resulting controller are fixed in orthonormal basis functions to obtain preferable convergence properties. Simulations show the effectiveness of the control strategy and the sensitivity for estimation errors in the poles. It is shown that disturbance rejection can be improved up to 40 dB by taking into account the internal air mount dynamics in the feedforward controller

Active Vibration Isolation by Model Reference Adaptive Control

This paper proposes model reference adaptive control (MRAC) to actively isolate payloads from floor vibrations and direct disturbance forces. Adaptive feedforward control is used to counteract measured disturbances, whereas an adaptive feedback controller suppresses unmeasured disturbances using skyhook damping. In the considered rigid single degree of freedom system, the ideal controller gains only depend on the stiffness and damping properties of the suspension. The MRAC strategy is validated experimentally on a hard mounted vibration isolation system. Attenuation of acceleration levels beyond −40 dB are obtained in a wide frequency band 5−100 Hz and the root-mean-square (RMS) acceleration in the frequency region of interest (0.1 − 100 Hz) is reduced 32 times with respect to passive isolation

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

\u3cp\u3eThis 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.\u3c/p\u3

Self-tuning feedforward control for active vibration isolation of precision machines

A novel feedforward control strategy is presented to isolate precision machinery from broadband floor vibrations. The control strategy aims at limiting the low-frequency controller gain, to prevent drift and actuator saturation, while still obtaining optimal vibration isolation performance at higher frequencies. This is achieved by limiting the low-frequency control action such that almost no phase shift is introduced at higher frequencies. To minimize model uncertainties, the feedforward controller is implemented as a self-tuning IIR filter that estimates the parameters online. Only a few parameters have to be estimated, which makes the algorithm computationally efficient. An additional feedback controller is designed to make the self-tuning algorithm more robust. The effects of feedforward and feedback control add up. The control strategy is successfully validated on an experimental setup of a vibration isolator

Self-tuning feedforward control for active vibration isolation of precision machines

A novel feedforward control strategy is presented to isolate precision machinery from broadband floor vibrations. The control strategy aims at limiting the low-frequency controller gain, to prevent drift and actuator saturation, while still obtaining optimal vibration isolation performance at higher frequencies. This is achieved by limiting the low-frequency control action such that almost no phase shift is introduced at higher frequencies. To minimize model uncertainties, the feedforward controller is implemented as a self-tuning IIR filter that estimates the parameters online. Only a few parameters have to be estimated, which makes the algorithm computationally efficient. An additional feedback controller is designed to make the self-tuning algorithm more robust. The effects of feedforward and feedback control add up. The control strategy is successfully validated on an experimental setup of a vibration isolator