Dr Yik Teo

Repetitive control (RC) achieves tracking and rejection of periodic exogenous signals by incorporating a model of a periodic signal in the feedback path. To improve the performance, an inverse plant response filter (IPRF) is used. To improve robustness, the periodic signal model is bandwidth-limited. This limitation is largely dependent on the accuracy of the IPRF. A new method is presented for synthesizing the IPRF for discrete-time RC. The method produces filters in a simpler and more consistent manner than existing best-practice methods available in the literature, as the only variable involved is the selection of a windowing function. It is also more efficient in terms of memory and computational complexity than existing methods. Experimental results for a nanopositioning stage show that the proposed method yields the same or better tracking performance compared to existing methods.

This article describes an improvement to integral resonance damping control (IRC) for reference tracking applications, such as scanning probe microscopy and nanofabrication. It is demonstrated that IRC control introduces a low-frequency pole into the tracking loop that is detrimental for performance. In this work, the location of this pole is found analytically using Cardano's method then compensated by parameterizing the tracking controller accordingly. This approach maximizes the closed-loop bandwidth while being robust to changes in the resonance frequencies. The refined IRC controller is comprehensively compared to other low-order methods in a practical environment.

Abstract This paper proposes an improvement to Integral Force Feedback (IFF), which is a popular method for active vibration control of structures and mechanical systems. Benefits of IFF include robustness, guaranteed stability and simplicity. However, the maximum damping performance is dependent on the stiffness of the system; hence, some systems cannot be adequately controlled. In this paper, an improvement to the classical force feedback control scheme is proposed. The improved method achieves arbitrary damping for any mechanical system by introducing a feed-through term. The proposed improvement is experimentally demonstrated by actively damping an objective lens assembly for a high-speed confocal microscope.

This paper describes a new vibration damping technique based on Integral Force Feedback (IFF). Classical IFF utilizes a force sensor and integral controller to damp the resonance modes of a mechanical system. However, the maximum modal damping depends on the frequency difference between the system's poles and zeros. If the frequency difference is small, the achievable modal damping may be severely limited. The proposed technique allows an arbitrary damping ratio to be achieved by introducing an additional feed-through term to the control system. This results in an extra degree of freedom that allows the position of the zeros to be modified and the maximum modal damping to be increased. The second contribution of this paper is a structured PI tracking controller that is parameterized to cancel the additional pole introduced by integral force feedback. The parameterized controller has only one tuning parameter and does not suffer from reduced phase margin. The proposed techniques are demonstrated on a piezoelectric objective lens positioner. The results show exceptional tracking and damping performance while maintaining insensitivity to changes in resonance frequency. The maximum bandwidth achievable with a commercial PID controller is 26.1 Hz. In contrast, with the proposed damping and tracking controller, the bandwidth is increased to 255 Hz. © 2014 Elsevier Ltd. All rights reserved.

Repetitive control (RC) is used to track and reject periodic exogenous signals by including a model of a periodic signal in the feedback path. The performance of RC can be improved by also including an. The accuracy of this filter is the main limitation to the RC bandwidth. The bandwidth is typically limited with a robustness filter - often a low-pass filter which attenuates the model at high-frequencies where the model-mismatch often occurs. In this paper, two robustness filter designs are compared. The first design is a brick-wall low-pass filter commonly used in the literature. The second design is based on the uncertainty between the inverse plant response filter and the measured response of the system. Experimental results demonstrate that the proposed method outperforms the traditional brick-wall filter approach.