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Author

Andreas Kotsopoulos

Other affiliations: IBM
Bio: Andreas Kotsopoulos is an academic researcher from University of Patras. The author has contributed to research in topics: Control theory & Data acquisition. The author has an hindex of 3, co-authored 9 publications receiving 56 citations. Previous affiliations of Andreas Kotsopoulos include IBM.

Papers
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Journal ArticleDOI
TL;DR: In this paper, a spiral trajectory nanopositioning scheme is proposed as an alternative to the conventional raster positioning pattern, which has an extremely narrowband frequency content, which shifts very slowly over time.

31 citations

Journal ArticleDOI
TL;DR: In this article, a spiral-enhanced tracking control architecture is presented for the constant linear velocity spiral case, which exploits the spire-wise narrowband frequency content of the reference signal, enabling very high speed and accurate positioning.

12 citations

Proceedings ArticleDOI
01 Dec 2010
TL;DR: Simulations show that the proposed architecture enables spiral scan operation with very low tracking error even at very high scan frequencies.
Abstract: Scanning probes are being considered as the basis for a variety of emerging nanoscale applications including sample imaging and ultra-high-density probe storage. In this work, a controller for track-follow in archimedean spiral nanopositioning is presented. The proposed tracking controller is based on a Linear Quadratic Gaussian (LQG) component and a tracking controller, extended with frequency-sliding peak filters in order to exploit the inherent properties of the spiral reference signal. Simulations show that the proposed architecture enables spiral scan operation with very low tracking error even at very high scan frequencies.

7 citations

Proceedings ArticleDOI
05 May 2009
TL;DR: In this paper, the authors focus on modeling the dynamics of MEMS-based mobile devices, when are subject to speed-controlled human motion, using measurements from accelerometers mounted on the device's frame.
Abstract: This work focuses on modeling the dynamics of MEMS-based mobile devices, when are subject to speed-controlled human motion, using measurements from accelerometers mounted on the device's frame. The measurement procedure and used data acquisition setup, indicative measurements showing the effect of physical system characteristics on the resulting acceleration signal diversity, the collected data analysis, as well as the selected modeling approach based on Hidden Markov Models (HMM) are presented and analyzed. Finally, simulation results of the proposed model's performance are discussed.

3 citations

Proceedings ArticleDOI
25 Jun 2006
TL;DR: A signal-to-noise ratio (SNR) estimation algorithm operating on BPSK modulated data targeted to multicarrier systems in additive white Gaussian noise channels on the C6711 digital signal processor (DSP) of Texas instruments (TI).
Abstract: The objective of this paper is to present the implementation and optimization process of a Signal-to-Noise Ratio (SNR) estimation algorithm operating on BPSK modulated data targeted to multicarrier systems in Additive White Gaussian Noise (AWGN) channels on the C6711 Digital Signal Processor (DSP) of Texas Instruments (TI). In our case, the algorithm was applied to an Orthogonal Frequency Division Multiplexing (OFDM) system. First, the basic structure of the algorithm was implemented and tested using plain C language and Matlab-generated OFDM samples for proof of concept reasons. Next, the code was ported on the DSP for implementation and optimization using DSP-specific C/Assembly, and embodied into a previously implemented, in our lab, OFDM transceiver running on the DSP. The optimization scheme followed was based on several optimization aspects, such as identifying and recoding the most time-consuming parts utilizing the target hardware's characteristics, as well as algorithmic modifications and compiler features. The correctness of the optimization was continuously verified at every optimization stage by providing to the estimator actual data having passed through the transceiver. Finally, a comparison of the implemented estimator with another implemented SNR estimator, in terms of execution speed and SNR estimation accuracy, is presented.

2 citations


Cited by
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Book ChapterDOI
Roy M. Howard1
01 Jan 2002
TL;DR: Chapter 8 establishes the relationship between the input and output power spectral densities of a linear system and the theory is extended to multiple input-multiple output systems.
Abstract: Chapter 8 establishes the relationship between the input and output power spectral densities of a linear system. Limitations on results are carefully detailed and the case of oscillator noise is considered. The theory is extended to multiple input-multiple output systems.

789 citations

Journal ArticleDOI
TL;DR: A procedure for tuning the spatial and the temporal resolution of Lissajous trajectories is presented and experimental results obtained on a custom-built atomic force microscope (AFM) are shown.
Abstract: A novel scan trajectory for high-speed scanning probe microscopy is presented in which the probe follows a two-dimensional Lissajous pattern The Lissajous pattern is generated by actuating the scanner with two single-tone harmonic waveforms of constant frequency and amplitude Owing to the extremely narrow frequency spectrum, high imaging speeds can be achieved without exciting the unwanted resonant modes of the scanner and without increasing the sensitivity of the feedback loop to the measurement noise The trajectory also enables rapid multiresolution imaging, providing a preview of the scanned area in a fraction of the overall scan time We present a procedure for tuning the spatial and the temporal resolution of Lissajous trajectories and show experimental results obtained on a custom-built atomic force microscope (AFM) Real-time AFM imaging with a frame rate of 1 frame s⁻¹ is demonstrated

154 citations

Journal ArticleDOI
TL;DR: In this paper, an improved model predictive control (MPC) scheme was proposed to increase the imaging speed of an atomic force microscope (AFM) using a spiral scanning method.
Abstract: An atomic force microscope (AFM) is an extremely versatile investigative tool in the field of nanotechnology, the performance of which is significantly influenced by its conventional zig-zag raster pattern scanning method. In this paper, in order to increase its imaging speed, we consider the use of a sinusoidal scanning method, i.e., a spiral scanning method with an improved model predictive control (MPC) scheme. In this approach, spirals are generated by applying waves, each with a single frequency and slowly varying amplitude, in the X-piezo (sine wave) and Y-piezo (cosine wave) of the piezoelectric tube scanner (PTS) of the AFM. As these input signals are single frequencies, the scanning can proceed faster than traditional raster scanning, without exciting the resonant mode of the PTS. The proposed MPC controller reduces the phase error between the reference position input and measured output sinusoids and provides better tracking of the reference signal. Also, a notch filter is designed and included in the feedback loop to suppress vibrations of the PTS at the resonant frequency. The experimental results show that, using the proposed method, the AFM is able to scan a 6 μm radius image within 2.04 s with a quality better than that obtained using the conventional raster pattern scanning method.

78 citations

Journal ArticleDOI
TL;DR: In this article, the authors considered the use of a high-speed spiral imaging technique with an improved multi-input multi-output (MIMO) model predictive control (MPC) scheme with a damping compensator for faster scanning by an atomic force microscope (AFM).
Abstract: One of the key barriers to an atomic force microscope (AFM) achieving high scanning speeds is its use of the traditional zig-zag raster pattern scanning technique. In this paper, we consider the use of a high-speed spiral imaging technique with an improved multi-input multi-output (MIMO) model predictive control (MPC) scheme with a damping compensator for faster scanning by an AFM. The controller’s design is based on an identified MIMO model of the AFM’s piezoelectric tube scanner (PTS) and it achieves a higher closed-loop bandwidth, significant damping of the resonant mode of the PTS, and reduces the cross-coupling effect between the PTS’s axes. The spirals produced have particularly narrow-band frequency measures which change slowly over time, thereby making it possible for the scanner to achieve improved tracking and continuous high-speed scanning rather than being restricted to the back and forth motion of raster scanning. To evaluate the performance improvement using this proposed control scheme for spiral scanning, an experimental comparison of its scanned images with those of the open-loop condition is performed. Experimental results show that, by using the proposed method, the AFM’s scanning speed is significantly increased up to 180 Hz.

66 citations

Journal ArticleDOI
TL;DR: A survey of the literature, an overview of a few emerging innovative solutions in AFM imaging, and future research directions are presented, which suggest a need to perform fast scans using an AFM with nanoscale accuracy.
Abstract: Nanotechnology is the branch of science which deals with the manipulation of matters at an extremely high resolution down to the atomic level. In recent years, atomic force microscopy (AFM) has proven to be extremely versatile as an investigative tool in this field. The imaging performance of AFMs is hindered by: 1) the complex behavior of piezo materials, such as vibrations due to the lightly damped low-frequency resonant modes, inherent hysteresis, and creep nonlinearities; 2) the cross-coupling effect caused by the piezoelectric tube scanner (PTS); 3) the limited bandwidth of the probe; 4) the limitations of the conventional raster scanning method using a triangular reference signal; 5) the limited bandwidth of the proportional-integral controllers used in AFMs; 6) the offset, noise, and limited sensitivity of position sensors and photodetectors; and 7) the limited sampling rate of the AFM's measurement unit. Due to these limitations, an AFM has a high spatial but low temporal resolution, i.e., its imaging is slow, e.g., an image frame of a living cell takes up to 120 s, which means that rapid biological processes that occur in seconds cannot be studied using commercially available AFMs. There is a need to perform fast scans using an AFM with nanoscale accuracy. This paper presents a survey of the literature, presents an overview of a few emerging innovative solutions in AFM imaging, and proposes future research directions.

58 citations