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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]

Dementia diagnosis often relies on expensive and invasive neuroimaging techniques that limit access to early screening. This study proposes an innovative approach for facilitating early dementia screening by estimating diffusion tensor imaging (DTI) measures using accessible lifestyle and brain imaging factors. Conventional DTI analysis, though effective, is often hindered by high costs and limited accessibility. To address this challenge, fuzzy subtractive clustering identified 14 influential variables from the Lifestyle for Brain Health and Brain Atrophy and Lesion Index frameworks, encompassing demographics, medical conditions, lifestyle factors, and structural brain markers. A multilayer perceptron (MLP) neural network was developed using these selected variables to predict fractional anisotropy (FA), a DTI metric reflecting white matter integrity and cognitive function. The MLP model achieved promising results, with a mean squared error of 0.000 878 on the test set for FA prediction, demonstrating its potential for accurate DTI estimation without costly neuroimaging techniques. The FA values in the dataset ranged from 0 to 1, with higher values indicating greater white matter integrity. Thus, a mean squared error of 0.000 878 suggests that the model's predictions were highly accurate compared to the observed FA values. This multifactorial approach aligns with the current understanding of dementia's complex etiology influenced by various biological, environmental, and lifestyle factors. By integrating readily available data into a predictive model, this method enables widespread, cost-effective screening for early dementia risk assessment. The proposed accessible screening tool could facilitate timely interventions, preventive strategies, and efficient resource allocation in public health programs, ultimately improving patient outcomes and caregiver burden. [ABSTRACT FROM AUTHOR]