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This article first reviews the position control of piezoelectric actuators, particularly charge-based sensorless control systems, which often include a charge estimator as a key component. The rest of the paper is about charge estimators for piezoelectric actuators. Two of the most recent/effective types of these estimators utilise either a sensing capacitor (type I in this paper) or a sensing resistor (type II); the latter (and the newer) type is broadly known as a digital charge estimator. Some experimental results in the literature show that, with the same loss in excitation voltage, a considerably higher amount of charge can be estimated with a type II estimator in comparison with a type I estimator; therefore, the superiority of type II estimators was acknowledged. In order to re-assess this conclusion, this paper equitably compares type I and II estimators through analytical modelling and experimentation. The results indicate that type II estimators have only a slight advantage in estimating higher amounts of charge, if both type I and II estimators are designed appropriately. At the same time, type II estimators have disadvantages; e.g., the resistance of type II estimators has to be tuned to suit different excitation frequencies. This research concludes that capacitor-based (type I) charge estimators for piezoelectric actuators, with pertinent design and implementation, can be still the prime solution for many charge estimation problems despite claims in the literature in the last decade. [ABSTRACT FROM AUTHOR]

In this research, a design guideline for a kinetic energy converter using a cantilever triple-layer piezoelectric harvester (CTLPH) for low-frequency applications is presented. By combining the constitutive and internal energy equations, the analytical equations for harvested voltage and power were developed. It was also found that frequency of motion, applied tip force, piezoelectric coefficients, geometrical dimensions, and mechanical properties of layers play significant roles in the performance of the harvester. Having characterised the voltage regulator module, LTC3588, the dependency of output voltage on both the storage and output capacitors of the LTC3588 was investigated. An experimental measurement using the optical method was carried out to determine the applied tip force. Furthermore, the performance of the CTLPH in low frequencies (<3.3 Hz) for various resistive loads was investigated. It was found that both excitation frequency and external resistance load are effective on the maximum generated power. The developed CTLPH shows the optimum power of 17.31 μ W at the external resistance of 20 kΩ, which is highly appropriate for micropower devices with at least 3.2 Hz of kinetic vibration in their environment. [ABSTRACT FROM AUTHOR]

Experiments have shown that, for an extensive area of operating, charge of a piezoelectric actuator is proportional to its displacement from relaxing state. Consequently, accurate estimation of charge can lead to position/displacement estimation for piezoelectric actuators, a prominent progress towards precise sensorless micro/nanopositioning. However, disadvantageously, all known charge estimators of piezoelectric actuators have electrical element(s), e.g. (a) resistor(s) or (a) capacitor(s), in series with the actuator. Such elements, known as sensing elements, take a considerable share of the excitation voltage. Voltage taken by the sensing elements is called voltage drop. Charge estimators with a resistor in series with the actuator (also known as digital charge estimators) have been reported to witness the smallest voltage drop. The aim of this paper is to design such charge estimators so as to achieve maximum precision at minimum possible voltage drop. The aforementioned aim is shown to be obtained when the range of the voltage across the resistor equals the narrowest input range of the analogue to digital convertor of the charge estimator. This, however, is impossible to happen for wide operating areas with a sensing resistor with unchangeable resistance, according to experimental results. The alternative is an adaptive charge estimator with a resistor, in which its resistance varies with operating conditions. This paper presents two methods to estimate such a varying sensing resistor: approximate analytical formulation and artificial intelligence, in which, the latter shows evident superiority. [ABSTRACT FROM AUTHOR]

This paper aims at introduction, design, and validation of a temperature estimation algorithm for an infrared dryer. The proposed algorithm estimates the temperature at one or some points in a thermal system (e.g., an infrared dryer) based on the measured temperature at a number of other points. In this research, the designed algorithm estimates the temperature of a single point; however, the methodology can be evidently extended to multiple points. Inspired by direct and inverse heat transfer models, a mathematical model is presented for this purpose. This model is developed and identified using artificial neural network (ANN) technique and laboratory experimental data. The proposed method exhibits excellent accuracy with no need to thermo-physical properties of the system. [ABSTRACT FROM AUTHOR]

This paper proposes a vibration-based fault-diagnosis method for mechanical parts. This method, after algorithm development, only requires a single inexpensive test to inspect the part which could take as short as half a second. The algorithm is developed in three major stages, (i) exciting specimens without or with known faults using a controlled force and recording acceleration of a single point for a short time (ii) finding a signature for each faulty specimen, using Fourier transform and statistical analysis. (iii) Developing a multi-layer perceptron, as a mathematical model, using the results of stage (ii). The elements of a part signature are the inputs to the model. The location (and possibly size and shape factor) of the fault is model output. Stage (i) can be performed experimentally or alternatively with a validated FEM, one experiment or simulation per specimen. The proposed technique was examined to locate (isolate) a fault on an automobile cylinder head. The presented accuracy is considerable, and the data collected at fairly low frequency range (below 1200 Hz) were found to be sufficient for this technique. In the case study of this paper, possible fault locations are on a line; as a result, fault location has one dimension. It is shown that the technique can be extended to higher dimensions. [ABSTRACT FROM AUTHOR]

This paper presents the idea of virtual temperature sensors for irradiative enclosures. Such a virtual sensor is an algorithm which receives the temperature of a number of points on surfaces of an enclosure and estimates the temperature of another point (or a number of other points) within enclosure. This paper proposes a data-driven method based on fuzzy inference systems to develop temperature virtual sensing algorithms. The proposed method is validated on an experimental setup exhibiting excellent estimation accuracy with no need to thermo-physical properties of the enclosure. In this research, the designed and validated algorithm estimates the temperature of a single point; however, the methodology can be evidently extended to multiple points. [ABSTRACT FROM AUTHOR]

• A new vibration reduction system using a magnetostrictive (Fe-Ga alloy) bimetal actuator is presented. • A novel disturbance rejection control scheme that eliminates an unknown disturbance, without needing knowledge of its dynamics is presented. • The principle of operation of the bimetal actuation mechanism is described. • The active anti-vibration system using a magnetostrictive bimetal actuator is fabricated based on analytical and FEM results and experimentally tested in different frequencies. • The developed control system demonstrates the capability of about 33.6 % reduction in vibration amplitude of the main system (the beam vibration amplitude). This paper introduces a new vibration reduction system using a magnetostrictive (Fe-Ga alloy) bimetal actuator. The proposed method (i) uses a magnetostrictive bimetal actuator instead of prevalent single material ones that need an auxiliary temperature control system and (ii) utilises a novel disturbance rejection control scheme that eliminates an unknown disturbance, without needing knowledge of its dynamics. In experiments, the vibration source is demonstrated as an unbalanced motor attached to the tip of a cantilever beam, resembling a beam-like element subject to ambiance vibrations. In the first step, the fundamental of this anti-vibration system is introduced and described. Then, analytical and data-driven modelling for the combination of the beam, the motor, and the bimetal is reported. These follow by model validation and impulse response analysis. Then, the proposed control system is introduced in detail. Experimental results indicate that the control system results in 33.6% decrease in beam vibration amplitude. Furthermore, the presented method in this paper can be employed as a design guideline for future applications. [ABSTRACT FROM AUTHOR]

Abstract: This paper offers a new hybrid position estimation method for the sensorless control of piezoelectric actuators. Often mathematical models which map easy to measure signals to displacement are used in this role. The proposed method is aimed at enhancing the accuracy of commonly accepted black box models. Three easy to measure signals are available to be used to estimate displacement. One, the induced voltage, is not suitable for piezoelectric stacks. Two others are more generally usable: the piezoelectric voltage and the sensing voltage. This paper proposes, then theoretically and experimentally verifies a hybrid algorithm that uses the two latter signals to produce estimates of displacement with improved accuracy. [Copyright &y& Elsevier]

In this article, different approaches of the use of black box modelling techniques for piezoelectric actuators are particularly addressed, regardless of the employed technique/algorithm. A modelling approach in this paper refers to two matters: the first, the role of black box techniques in modelling (i.e. if physics-based techniques are also involved in modelling; if so, how and to what extent). From this aspect, the spectrum of approaches ranges from those merged with/inspired by classical phenomenological models to an approach based on purely system identification-based techniques. The second aspect of modelling approaches, in this article, is the input variables to the model. Current and previous values of input voltage, previous values of the output (displacement), derivatives and extremum values of the system's input/output have been used as the inputs to the model so far. Both aforementioned aspects of modelling approaches are addressed appropriately in this article, and various modelling approaches in the literature are categorized and presented in a uniform and comparable manner, so that readers can easily identify research trends in this area and the gaps in the literature. One of the identified unanswered questions in the literature is whether the extremum values of the system's input/output should/should not be used as an input to black box models of piezoelectric actuators. There are works in the literature which have/have not used the aforementioned input variables, but there is no published investigation to evidently answer the proposed question. This article, in the last section, answers this question by reporting and discussing an experimental study. [ABSTRACT FROM AUTHOR]

Abstract: In this work, a new solution approach was developed for heat estimation class of inverse heat transfer problems where radiation provides the dominant mode thermal energy transport. An Artificial Neural Network (ANN) was designed, trained and employed to estimate the heat emitted to irradiative batch drying process. In a simple laboratory drying furnace, various input signals (different input power functions) were input to the dryer''s halogen lamp and the resulting temperature history were measured and recorded for a point on the bottom surface of the dryer. After estimating the order, the sampling time and the dead-time of the system, the recorded data were arranged for inverse modelling purposes. Next, an artificial neural network (ANN) was designed and trained to play the role of the inverse heat transfer model. The results showed that ANNs are applicable to solve inverse heat estimation problems of irradiative batch drying process. An important advantage of this method in comparison with classical inverse heat transfer modelling approaches, detailed knowledge of the geometrical and thermal properties of the system (such as wall conductivity, emissivity , etc.) is not necessary. Such properties are difficult to measure and may undergo significant changes during the temperature transient. [Copyright &y& Elsevier]

Abstract: This paper deals with modeling a power plant component with mild nonlinear characteristics using a modified neural network structure. The hidden layer of the proposed neural network has a combination of neurons with linear and nonlinear activation functions. This approach is particularly suitable for nonlinear system with a low grade of nonlinearity, which can not be modeled satisfactorily by neural networks with purely nonlinear hidden layers or by the method of least square of errors (the ideal modeling method of linear systems). In this approach, two channels are installed in a hidden layer of the neural network to cover both linear and nonlinear behavior of systems. If the nonlinear characteristics of the system (i.e. de-superheater) are not negligible, then the nonlinear channel of the neural network is activated; that is, after training, the connections in nonlinear channel get considerable weights. The approach was applied to a de-superheater of a 325MW power generating plant. The actual plant response, obtained from field experiments, is compared with the response of the proposed model and the responses of linear and neuro-fuzzy models as well as a neural network with purely nonlinear hidden layer. A better accuracy is observed using the proposed approach. [Copyright &y& Elsevier]

As a first endeavour, nonlinear dynamic response of the glass fibre-reinforced​ epoxy (GRE) laminated composite cylindrical shells under an impulse load is investigated based on the first-order shear deformation theory (FSDT) of shells. Green's strain and von Kármán hypothesis are assumed to consider the geometrical nonlinearity due to large deformation in the model. A new solution procedure composed of the differential quadrature method (DQM) based on the direct projection of the Heaviside function and a non-uniform rational B-spline (NURBS) based multi-step time integration scheme is employed to discretize the governing equations in the spatial and temporal domains, respectively. The approach is validated by showing its fast convergence rate and performing comparison studies with available solutions in the limited available cases. A comprehensive parametric study is performed then on the model and the effects of the geometrical parameters, number of layers, load location, time durations, and types of impulse loading on the nonlinear dynamic responses of GRE laminated composite cylindrical shells are investigated. • Nonlinear dynamic response of cylindrical shells under impulse loading is studied. • Cylindrical shells are made of GRE reinforced composite layers. • FSDT theory and Hamilton's principle are employed to formulate the problem. • A new coupled DQ-Heaviside technique is presented to discretize spatial domain. • A NURBS based multi-step method is used for the solution of nonlinear ODEs. [ABSTRACT FROM AUTHOR]

In this paper, a Neuro-Predictive (NP) controller was first designed and implemented on a highly non-linear system, a model helicopter in a constrained situation. It was observed that the closed loop system with the NP controller had a significant overshoot and a long settling time in comparison to the same system with an fuzzy controller. In order to improve the system's performance, a Sugeno-type fuzzy compensator, having only two rules, is added to the control loop to adjust control input. The newly designed Neuro-Predictive control with the Fuzzy Compensator (NPFC) improves the system's performance. Furthermore, it is shown that the NPFC controlled system is robust to disturbance and system parameter changes. [ABSTRACT FROM AUTHOR]

Abstract: In this paper the neural networks is utilized to estimate the “filter coefficients” needed to estimate heat flux in a particular system. In developing the training phase of the network inspiration is drawn from the Burgraff''s exact solution of the IHCP as well as the filter method. Thus, the estimation phase neither requires any temperature field nor the sensitivity coefficients calculations. The neural network used in this work is a 2-layer perceptron. It is shown via classical triangular heat flux test cases that the method can yield very accurate, very efficient as well as stable estimations. [Copyright &y& Elsevier]

In this paper, dynamic response of multilayer functionally graded graphene platelets reinforced composite (FG-GPLRC) cylindrical shells in thermal environment under an impulse load is studied based on the first order shear deformation theory (FSDT) of shells. The cylindrical shells under consideration are made up of multiple graphene platelet reinforced composite (GPLRC) layers with uniformly distributed and randomly oriented graphene platelets (GPLs) in each layer. GPL concentration is assumed to be graded in thickness direction. A new differential quadrature method based on direct projection of the Heaviside function is utilized to spatially discretize the governing equations. To solve the resulting system of ordinary differential equations (ODE) in temporal domain, a recently developed multi-step time integration technique, introduced based on the non-uniform rational B-spline (NURBS), is employed. After validating the approach, the effects of the different GPLs distribution patterns, the weight fraction and dimension ratios of the GPLs, temperature change, time durations and types of impulse loading on the dynamic responses of the FG-GPLRC shells are investigated and discussed. It is shown that the addition of only little GPLs to polymer matrix considerably decreases the period of oscillatory portions of the center deflection. • Dynamic response of cylindrical shells under impulse loading is studied. • Cylindrical shells are made of multilayer FG-GPLRC. • Presenting a new DQM based on direct projection of the Heaviside function. • The problem is formulated based on the first order shear deformation theory. • A multi-step NURBS-based method is used to discretize temporal domain. [ABSTRACT FROM AUTHOR]

This article presents the development of a cantilever harvester made of permendur with tip excitation. In the beginning, the dynamic behavior of the tip-mass beam harvester subjected to a harmonic bending force at the free-end has been studied. Also, the magneto-mechanical model, rotating unbalance equations and Faraday's Law have been combined to present the general model for generated power. Furthermore, damping coefficients have been elaborately measured and considered in the modeling of magnetostrictive harvester and prediction of optimum load to generate the maximum power. Good agreement between analytical and experimental results shows that the model is able to predict the behavior of harvester under the vibration with tip excitation and can find the optimum external load to have maximum power. Experiment results show that the maximum output power is 6.81 μW/cm3 and this power happens when the harvester is connected to a 0.63 Ω external load. Compared to other magnetostrictive harvesters, Permendur shows lower power density. However, its harvested power is enough to energize μW electrical devices at a reasonable cost. The presented results in this paper can be utilized as a design guideline for future investigations to optimize vibration-based magnetostrictive energy harvesters with tip excitation. • Modeling of a cantilever Permendur harvester with tip excitation has been presented. • An elaborate method to specify the damping coefficient of the harvester is introduced. • The output power is comparable with electrostatic energy harvesters. • The Permendur harvester is suitable to energize μW devices with low resistive load. [ABSTRACT FROM AUTHOR]

Highlights: [•] A grounded-load digital charge-based displacement estimator (GDCDE) is presented. [•] An artificial neural network (ANN) was also designed to estimate the piezoelectric tube's displacement using the piezoelectric voltage at low frequencies of excitation. [•] A complementary filter combines the proposed GDCDE and the ANN to estimate displacement over a wide bandwidth and to overcome drift. [•] The discrepancy between the desired and estimated displacement is fed back to the piezoelectric actuator using proportional control. [Copyright &y& Elsevier]

Abstract: In this work system identification techniques are used to map the two-dimensional heat flux into the temperatures through a linear model supported by theoretical and numerical results. The basis of this analysis is a discrete version of the Burggraf Method saying a single component heat flux is a linear combination of the temperatures around the time of its occurrence. Taking the same approach, a linear model (i.e. a linear artificial neural network (ANN)) is employed to estimate a multicomponent heat flux as a linear function of the temperatures. A known heat flux is imposed to the direct model, then the history of heat flux-temperature data are fit to the linear mathematical model (i.e. a linear ANN) using system identification techniques. The achieved model estimates the heat flux based on a series of past and future temperatures and the estimated heat flux components are in a good agreement with the exact ones. Finally, the effect of some important factors on the results is investigated. The proposed solution to inverse heat conduction problems does not need thermophysical and geometrical parameters of the system and is robust against noises. It merely needs some series of heat flux-temperature data from solution of a reliable direct numerical model or experiment. [Copyright &y& Elsevier]