Ma Michiel Beijen

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.

Performance trade-offs in disturbance feedforward compensation of active hard-mounted vibration isolators

With disturbance feedforward compensation (DFC), input disturbances are measured and compensated to cancel the effect of the disturbance. Perfect cancellation is not possible in practice due to the causal nature of DFC, in which the compensation generally comes too late. Therefore, non-perfect plant inversion, controller discretization and sensor dynamics lead to a non-zero residual error. The properties of this residual error are described in the frequency domain using a theoretical framework that is closely related to the design constraints known from filtering theory. It is shown that, like in feedback control systems, performance limitations of DFC systems are described by a waterbed effect. An experimental validation is included to demonstrate the properties of the residual error on an active hard-mounted vibration isolation setup.

Self-tuning disturbance feedforward control with drift prevention for air mount systems

A MIMO disturbance feedforward control strategy is presented to isolate an industrial active vibration isolation system with air mounts from broadband floor vibrations. The feedforward controller compensates for the static damping and stiffness of the air mount suspension, leading to significant improvement of the vibration isolation performance. At low frequencies the controller gain is limited using higher-order weak integrators to prevent drift and actuator saturation. To minimize performance limitations due to model uncertainties, the MIMO feedforward controller is implemented as an IIR filter with fixed poles and self-tuning zeros, having the ability to fine-tune the parameters online using a combination of filtered-ϵ least mean squares (FϵLMS) optimization and residual noise shaping. An experimental validation on a full-scale vibration isolation system with air mounts shows performance improvements up to 30 dB for frequencies between 30 and 80 Hz.

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.

Evaluating performance of multivariable vibration isolators: A frequency domain identification approach applied to an industrial AVIS

Vibration isolation is essential for industrial high-precision systems in suppressing the influence of external disturbances. The aim of this paper is to develop an identification method to estimate the transmissibility matrix for such systems. The transmissibility matrix is a key performance indicator in vibration isolation, but its identification is severely limited by the heavy weight and size of many industrial systems. Two non-parametric system identification methods based on periodic and spectral analysis are compared. It is shown that spectral analysis can benefit from random floor excitations at low frequencies and periodic shaker excitations at high frequencies. Using this method, a transmissibility matrix between 1 and 100 Hz is successfully measured on an industrial active vibration isolation system (AVIS), demonstrating that the proposed method is suitable for identification of these heavy-weight systems.