Mohsen Bazghaleh

Intelligent modeling of a piezoelectric tube actuator

Various model-based control methods are currently used in control of piezoelectric tubes, others such as internal model control and model predictive control are anticipated to be employed soon. All these control systems are designed based on black box models. However, systematic black box modeling of piezoelectric tubes has been overlooked in the literature to a large extent or has been presented in a too brief and faulty way. In this article, a novel structure of artificial neural networks is used to model and to assess the nonlinearity of piezoelectric actuators. Apart from nonlinearity, other features of the achieved models like delay time, sampling time, orders as well as system identification process are clearly stated, and more importantly, it is clarified that different definitions of accuracy are needed for different purposes of black box modeling, with change in model features, the accuracy may decrease for one purpose (e.g. predictive control) and increase for another one (e.g. simulation). This highly critical point has never been raised and addressed in modeling of piezoelectric tubes, and a definition of accuracy which suits static systems/models has been widely used in the past to assess models of piezoelectric tubes which are obviously dynamic. Experimental results support the proposed modeling ideas.

Implementation and analysis of an innovative digital charge amplifier for hysteresis reduction in piezoelectric stack actuators

Smart actuators are the key components in a variety of nanopositioning applications, such as scanning probe microscopes and atomic force microscopes. Piezoelectric actuators are the most common smart actuators due to their high resolution, low power consumption, and wide operating frequency but they suffer hysteresis which affects linearity. In this paper, an innovative digital charge amplifier is presented to reduce hysteresis in piezoelectric stack actuators. Compared to traditional analog charge drives, experimental results show that the piezoelectric stack actuator driven by the digital charge amplifier has less hysteresis. It is also shown that the voltage drop of the digital charge amplifier is significantly less than the voltage drop of conventional analog charge amplifiers.

IMC-based feedforward control of a piezoelectric tube actuator

This article addresses sensorless control of a piezoelectric tube actuator to avoid the expense and practical limits of displacement sensors in nanopositioning. Three electrical signals have been used to estimate displacement: the piezoelectric voltage, the induced voltage and the sensing voltage. In this work, the piezoelectric voltage was employed to estimate displacement which does not require drift removal like the sensing voltage and does not suffer from a time lag respect to displacement like the induced voltage. This signal is the actuating signal at the same time, so the sensorless control system is feedforward. It was shown the relationship between the piezoelectric actuator and displacement is nearly linear at the designated operation area: excitation of the tube by triangular voltage functions with the magnitude up to 60V and the frequency up to 60Hz. Therefore, Internal Model Control (IMC) was employed to design this feedforward controller based on a second order linear discrete model which maps the piezoelectric voltage into displacement. The performance of the proposed feedforward controller has been compared with a well-tuned feedforward P-action controller and a remarkable improvement has been observed.

A digital charge amplifier for hysteresis elimination in piezoelectric actuators

Piezoelectric actuators are commonly used for nanopositioning due to their high resolution, low power consumption and wide operating frequency, but they suffer hysteresis, which affects linearity. In this paper, a novel digital charge amplifier is presented. Results show that hysteresis is reduced by 91% compared with a voltage amplifier, but over long operational periods the digital charge amplifier approach suffers displacement drift. A non-linear ARX model with long-term accuracy is used with a data fusion algorithm to remove the drift. Experimental results are presented.

Physics-based modelling of a piezoelectric actuator using genetic algorithm

A number of models have been presented to estimate the displacement of piezoelectric actuators; these models remove the need for accurate displacement sensors used in nanopositioning. Physics based models, inspired by physical phenomena, are widely used for this purpose due to their accuracy and comparatively low number of parameters. The common issue of these models is the lack of a non-ad-hoc and reliable method to estimate their parameters. Parameter identification of a widely accepted physics-based model, introduced by Voigt, is addressed in this paper. Non-linear governing equation of this model consists of five parameters needing to be identified. This research aims at developing/adopting an optimal and standard (non-ad-hoc) parameter identification algorithm to accurately determine the parameters of the model and, in a more general view, all physics-based models of piezoelectric actuators. In this paper, Genetic Algorithm (GA) which is a global optimisation method is employed to identify the model parameters.

A system identification approach to the characterization and control of a piezoelectric tube actuator

This paper addresses the sensorless control of piezoelectric tube actuators to avoid the expense and practical limits of displacement sensors in nanopositioning applications. Three electrical signals have traditionally been used to estimate displacement: the piezoelectric voltage, the voltage induced in sensing electrodes and the voltage across a sensing resistor. In this work, the piezoelectric voltage was employed to estimate displacement; the use of this signal does not necessitate drift removal like the sensing voltage, and its superiority over the induced voltage is shown in this paper. The piezoelectric voltage is the actuating signal, so a feedforward architecture based on an inverse model is used for sensorless control. Inspired by internal model control (IMC), a filter together with the inverted model of the system, derived using system identification techniques, was used as the feedforward controller. The fixed-slope-input effect is illustrated as a prominent source of control error in tracking triangular references, then an additional nonlinear control command is proposed to address this effect and improve the control performance.

A review of charge methods for driving piezoelectric actuators

Piezoelectric actuators are the most commonly used actuators in nanopositioning. They provide excellent operating bandwidth and precision. These actuators are normally driven by voltage amplifiers; however, the relationship of the applied voltage on the actuator and its position is nonlinear and complex due to phenomena such as hysteresis. This adversely influences actuator’s position control which is the core component of nanopositioning. However, the electrical charge applied on a piezoelectric actuator has a significantly less complex relationship with its position. As a result, driving piezoelectric actuators with charge amplifiers has attracted significant attention. In this article, charge driving methods are classified, and their advantages, major issues and the solutions to these issues are critically reviewed.

Using frequency-weighted data fusion to improve the performance of a digital charge amplifier

Piezoelectric actuators are the most common among a variety of smart actuators due to their high resolution, low power consumption and wide operating frequency but they suffer hysteresis which affects linearity. In this paper a novel digital charge amplifier is presented which reduces hysteresis and linearizes the piezoelectric actuator. A frequency-weighted data fusion algorithm uses a non-linear ARX model to remove drift and increase the bandwidth of digital charge amplifier. Experimental results are presented.

A measurement study of cognitive radio spectrum sensing methods

As wireless devices proliferate, more of these devices have to share a finite and increasingly limited amount of available radio spectrum. Currently, spectrum bands are used for a particular purpose that they are licensed for. However, these spectrums are not always used by their licensees or primary users, and as such are unused and are idle most of the time. These swath of unused frequency spectrum can be used by unlicensed users, when available, to mitigate the spectrum scarcity. In this article we study different methods of spectrum sensing in cognitive radio paradigm and compare them in terms of their potential interference with primary users.