Chemical processes use to be non-minimum phase systems. Thereby, they are a challenge for control applications. In this paper, fuzzy state feedback is applied in the Van de Vusse reaction that has an inverse response. The control design has an integrator to enhance the control performance by eliminating the steady-state error when a step reference is applied. An anti-windup action is used to reduce the undershoot in the system response. In practice, it is not possible to have always access to all the state variables. Thus, a fuzzy state observer is implemented via LMIs. Frequently, the papers that show similar applications present some comments about disturbance rejection. To eliminate the steady-state error when a ramp reference is used, in this work, a second integrator is aggregated. Now, the anti-windup also reduces the overshoot generated due to the usage of two integrators in the final application.

This paper presents a fault-tolerant control scheme for a 2 DOF helicopter. The 2 DOF helicopter is a higher-order multi-input multi-output system featuring non-linearity, cross-coupling, and unstable behaviour. The impact of sensor, actuator, and component faults on such highly complex systems is enormous. This work employs sliding mode control, which is based on reaching and super-twisting laws, to handle the problem of fault control. Simulation tests are carried out to show the effectiveness of the algorithms. Various performance metrics are analyzed and the results show SMC based on super-twisting law provides better control with less chattering. The stability of the closed-loop system is mathematically assured, in the presence of faults, which is a key contribution of this research.

In this paper, an automatic voltage regulator (AVR) embedded with fractional order PID (FOPID) is employed for the alternator terminal voltage control. A novel meta-heuristic technique, a modified version of grey wolf optimizer (mGWO) is proposed to design and optimize the FOPID AVR system. The parameters of FOPID, namely, proportional gain ( Κ _Ρ), the integral gain ( Κ _I), the derivative gain ( Κ _D), λ and μ have been optimally tuned with the proposed mGWO technique using a novel fitness function. The initial values of the Κ _Ρ, Κ _I , and Κ _D of the FOPID controller are obtained using Ziegler-Nichols (ZN) method, whereas the initial values of λ and μ have been chosen as arbitrary values. The proposed algorithm offers more benefits such as easy implementation, fast convergence characteristics, and excellent computational ability for the optimization of functions with more than three variables. Additionally, the hasty tuning of FOPID controller parameters gives a high-quality result, and the proposed controller also improves the robustness of the system during uncertainties in the parameters. The quality of the simulated result of the proposed controller has been validatedby other state-of-the-art techniques in the literature.

This study analyses the performances of various path controlling strategies for a 3-degrees of freedom wrist exoskeleton, by comparing key indicators, such as rise time, steady-state error, and implementation difficulty. A model was built to describe both system’s kinematics and dynamics, as well as 3 different controllers (PID, PD¸, and a hybrid force/position controller) that were designed to allow each joint to perform smooth motions within anatomic ranges. The corresponding simulation was run and assessed via Matlab (version 2020a). In addition to the performance comparison, remarkable characteristics could be identified among controllers. PD¸ showed higher response speed than the other controllers (about 4 times), and PID was reinforced as the technique with the easiest implementation due to the smallest matrices. The study also allowed to greater potential of the hybrid controller to interact with its environment, i.e., the robotic device.

In this article we focus on optimal control problems involving a nonlinear fractional control system of different orders with Caputo derivatives, associated to a Lagrange cost functional. Based on a lower closure theorem for orientor fields combined with Filippov’s approach, we derive an existence result for at least one optimal solution for such a problem.

In this paper we deal with the problem of uniform exponential stabilization for a class of distributed bilinear parabolic systems with time delay in a Hilbert space by means of a bounded feedback control. The uniform exponential stabilization problem of such a system reduces to stabilizing only its projection on a suitable finite dimensional subspace. Furthermore, the stabilizing feedback control depends only on the state projection on the finite dimensional subspace. An explicit decay rate estimate of the stabilized state is given provided that a nonstandard weaker observability condition is satisfied. Illustrative examples for partial functional differential equations are displayed.

In this paper we prove the exact controllability of a time varying semilinear system considering non-instantaneous impulses, delay, and nonlocal conditions occurring simultaneously. It is done by using the Rothe’s fixed point theorem together with some sub-linear conditions on the nonlinear term, the impulsive functions, and the function describing the nonlocal conditions. Furthermore, a control steering the semilinear system from an initial state to a final state is exhibited.

The primary objective of this paper is the custom design of an effective, yet relatively easyto- implement, predictive control algorithm to maintain normoglycemia in patients with type 1 diabetes. The proposed patient-tailorable empirical model featuring the separated feedback dynamics to model the effect of insulin administration and carbohydrate intake was proven to be suitable for the synthesis of a high-performance predictive control algorithm for artificial pancreas.Within the introduced linear model predictive control law, the constraints were applied to the manipulated variable in order to reflect the technical limitations of insulin pumps and the typical nonnegative nature of the insulin administration. Similarly, inequalities constraints for the controlled variable were also assumed while anticipating suppression of hypoglycemia states during the automated insulin treatment. However, the problem of control infeasibility has emerged, especially if one uses too tight constraints of the manipulated and the controlled variable concurrently. To this end, exploiting the Farkas lemma, it was possible to formulate the helper linear programming problem based on the solution of which this infeasibility could be identified and the optimality of the control could be restored by adapting the constraints. This adaptation of constraints is asymmetrical, thus one can force to fully avoid hypoglycemia at the expense of mild hyperglycemia. Finally, a series of comprehensive in-silico experiments were carried out to validate the presented control algorithm and the proposed improvements. These simulations also addressed the control robustness in terms of the intersubject variability and the meal announcements uncertainty.

The linguistic q-rung orthopair fuzzy (L q-ROF) set is an important implement in the research area in modelling vague decision information by incorporating the advantages of q- rung orthopair fuzzy sets and linguistic variables. This paper aims to investigate the multicriteria decision group decision making (MCGDM) with L q-ROF information. To do this, utilizing Hamacher t-norm and t-conorm, some L q-ROF prioritized aggregation operators viz., L q- ROF Hamacher prioritized weighted averaging, and L q-ROF Hamacher prioritized weighted geometric operators are developed in this paper. The defined operators can effectively deal with different priority levels of attributes involved in the decision making processes. In addition, Hamacher parameters incorporated with the proposed operators make the information fusion process more flexible. Some prominent characteristics of the developed operators are also wellproven. Then based on the proposed aggregation operators, an MCGDM model with L q-ROF context is framed. A numerical example is illustrated in accordance with the developed model to verify its rationality and applicability. The impacts of Hamacher and rung parameters on the achieved decision results are also analyzed in detail. Afterwards, a comparative study with other representative methods is presented in order to reflect the validity and superiority of the proposed approach.

In the paper, the application of multi-criteria optimization of the parameters of PSS3B system stabilizers to damping electromechanical swings in an extended power system (PS) is presented. The calculations of the power system stabilizer (PSS) parameters were divided into two stages. In the first stage, single-machine systems, generating unit – infinite bus, of generating units critical for the angular stability of the PS were analyzed. Time constants and preliminary values of the PSS gains were calculated. In the second stage, the main one, the main gains on which the effectiveness of operation of PSSs depends the most were calculated by multi-criteria optimization of the extended PS. The calculations were carried out in several variants: for two-dimensional objective functions and the six-dimensional objective function. In multi-criteria optimization, the solution is not one set of PSS parameters, but a set of sets of these parameters, i.e. a set of compromises that were determined for each analyzed case. Additionally, for the six-dimensional compromise set, projections of this set on the planes connected with the quantities of individual generating units and the boundary of these projections on these planes were determined. A genetic algorithm adapted to multi-criteria issues was used to minimize the multivariate objective function. Sample calculations were made for the model of the National (Polish) Power System taking into account 57 selected generating units operating in high and extra high voltage networks (220 and 400 kV). The presented calculations show that the applied multi-criteria optimization of the PSS3B stabilizer parameters allows effectively damping electromechanical swings withoutworsening the voltagewaveforms of generating units in the extended PS.

We describe construction and investigation results of optical trace gas sensor working in the 3.334–3.337 μm spectral range. Laser spectroscopy was performed with a multipass cell. A setup was elaborated for detection of ethane at the 3.3368035 μm absorption line. Analysis of the gas spectra and the experiment have shown that, beside C2H6, the sensor is suitable for simultaneous detection of methane, formaldehyde and water vapor. Due to nonlinearity of the laser power characteristic we decided to detect the fourth harmonic of signal. Additional laser wavelength modulation was applied for optical interference suppression. In result, the precision of ethane detection of approximately 80 ppt has been achieved for the averaging time of 20 seconds. Long-term stability as well as the measurement linearity have also been positively tested. The system is suitable for detecting potential biomarkers directly in human breath.

Capacitive leakage and adjacent interference are the main influence sources of the measuring error in the traditional series step-up method. To solve the two problems, a new algorithm was proposed in this study based on a three-ports network. Considering the two influences, it has been proved that response of this three-ports network still has characteristics of linear superposition with this new algorithm. In this threeport network, the auxiliary series voltage transformers use a two-stage structure that can further decrease measurement uncertainty. The measurement uncertainty of this proposed method at 500/√3 kV is 6.8 ppm for ratio error and 7 μrad for phase displacement ( k = 2). This new method has also been verified by comparing its results with measurement results of the PTB in Germany over the same 110/√3 kV standard voltage transformer. According to test results, the error between the two methods was less than 2.7 ppm for ratio error and 2.9 μrad for phase displacement.

Different temperature sensors show different measurement values when excited by the same dynamic temperature source. Therefore, a method is needed to determine the difference between dynamic temperature measurements. This paper proposes a novelty approach to treating dynamic temperature measurements over a period of time as a temperature time series, and derives the formula for the distance between the measurement values using uniformsampling within the time series analysis. The similarity is defined in terms of distance to measure the difference. The distance measures were studied on the analog measurement datasets. The results show that the discrete Fréchet distance has stronger robustness and higher sensitivity. The two methods have also been applied to an experimental dataset. The experimental results also confirm that the discrete Fréchet distance performs better.

In dentistry, 3D intraoral scanners (IOSs) are gaining increasing popularity in the production of dental prostheses. However, the quality of an IOS in terms of resolution remains the determining factor of choice for the practitioner; a high resolution is a quality parameter that can reduce error in the production chain. To the best of our knowledge, the evaluation of IOS resolution is not clearly established in the literature. This study provides a simple assessment of resolution of an IOS by measuring a reference sample and highlights various factors that may influence the resolution. A ceramic tip was prepared to create a very thin object with an edge smaller than the current resolution stated by the company. The sample was scanned with microCT (micro-computed tomography) and an IOS. The resulting meshes were compared. In the mesh obtained with the IOS, the distance between two planes on the edge was approximately 100 micrometers, and that obtained with microtomography was 25 micrometers. The curvature values were 27.46 (standard deviation – SD) 14.71) μm ^-1 and 5.18 (SD 1.16) μm ^-1 for microCT and IOS, respectively. These results show a clear loss of information for objects that are smaller than 100 μm. As there is no normalized procedure to evaluate resolution of IOSs, the method that we have developed can provide a positive parameter for control of IOSs performance by practitioners.

Adjustable-width pulse signals are widely used in systems such as test equipment for hold time, response time and radar testing. In this study, we proposed a pulse generation method based on virtual sampling with ultra-high pulse width resolution. In the proposed method, the sampling rate of a digital-to-analogue converter (DAC) was adjusted to considerably improve pulse width resolution. First, the sampling rate was matched with the target pulse width resolution to digitally sample the ideal signal and generate digital waveform sampling points. Next, the signal bandwidth of the DAC was matched using a low-pass digital filter. Finally, the waveform sampling points were downsampled using an integer factor and output after digital-to-analogue conversion. The waveform pulse width information generated by high-frequency digital sampling was passed step by step and retained in the final output analogue signal. A DAC with a sampling rate of 1.25 GSa/s was used, and the pulse width resolution of the pulse signal was 0.1 ns. Theoretically, a sampling rate of 10 GSa/s is required to achieve 0.1 ns resolution. This method is simple, has a low cost, and exhibits excellent performance.

The cognitive aspects like perception, problem-solving, thinking, task performance, etc., are immensely influenced by emotions making it necessary to study emotions. The best state of emotion is the positive unexcited state, also known as the HighValence LowArousal (HVLA) state of the emotion. The psychologists endeavour to bring the subjects from a negatively excited state of emotion (Low Valence High Arousal state) to a positive unexcited state of emotion (High Valence Low Arousal state). In the first part of this study, a four-class subject independent emotion classifier was developed with an SVM polynomial classifier using average Event Related Potential (ERP) and differential average ERP attributes. The visually evoked Electroencephalogram (EEG) signals were acquired from 24 subjects. The four-class classification accuracy was 83% using average ERP attributes and 77% using differential average ERP attributes. In the second part of the study, the meditative intervention was applied to 20 subjects who declared themselves negatively excited (in Low Valence High Arousal state of emotion). The EEG signals were acquired before and after the meditative intervention. The four-class subject independent emotion classifier developed in Study 1 correctly classified these 20 subjects to be in a negatively excited state of emotion. After the intervention, 16 subjects self-assessed themselves to be in a positive unexcited (HVLA) state of emotion (which shows the intervention accuracy of 80%). Testing a four-class subject independent emotion classifier on the EEG data acquired after the meditative intervention validated 13 of 16 subjects in a positive unexcited state, yielding an accuracy of 81.3%.

Vibration analysis for conditional preventive maintenance is an essential tool for the industry. The vibration signals sensored, collected and analyzed can provide information about the state of an induction motor. Appropriate processing of these vibratory signals leads to define a normal or abnormal state of the whole rotating machinery, or in particular, one of its components. The main objective of this paper is to propose a method for automatic monitoring of bearing components condition of an induction motor. The proposed method is based on two approaches with one based on signal processing using the Hilbert spectral envelope and the other approach uses machine learning based on random forests. The Hilbert spectral envelope allows the extraction of frequency characteristics that are considered as new features entering the classifier. The frequencies chosen as features are determined from a proportional variation of their amplitudes with the variation of the load torque and the fault diameter. Furthermore, a random forest-based classifier can validate the effectiveness of extracted frequency characteristics as novel features to deal with bearing fault detection while automatically locating the faulty component with a classification rate of 99.94%. The results obtained with the proposed method have been validated experimentally using a test rig.

In this work, the electromotive force (EMF) near a permanent magnet heating cylinder was determined using a practical test bench. The aim is to elaborate three-dimensional analytical calculation capable of predicting accurately the same electromagnetic quantities by calculating the induced EMF in the presence of an inductive sensor. The analytical approach is obtained from developing mathematical integrals using the Coulombian approach to permanent magnets. In this approach, rotations are considered by Euler’s transformations matrices permitting the calculation of all permanent magnets flux densities contributions at the same points in the surrounding free space. These points, part of a uniform rectangular grid of the active EMF sensor surface, are used to compute the EMF by Faraday’s law. The validation results between experimental and simulated ones confirm the robustness and the efficiency of the proposed analytical approach.

Optically stimulated luminescence (OSL) and thermoluminescence (TL) methods are commonly used in dosimetry of ionizing radiation and dating of archaeological and geological objects. A typical disadvantage of OSL detectors is signal loss over a longer time scale. In this article, we present a method of studying this phenomenon as well as monitoring the state of the detector by means of optical sampling. The method was used to determine the OSL signal loss (fading) characteristics of selected potassium feldspars.

With the rapid development of industry, abundant industrial waste has resulted in escalating environmental issue. Steel slag is the by-product of steel-making and can be used as cementitious materials in construction. However, the low activity of steel slag limits its utilization. Much investigation has been conducted on steel slag, while only a fraction of the investigation focuses on the effect of steel slag particle size on the properties of mortar. The aim of this study is to investigate the effect of steel slag particle size as cement replacement on properties of steel slag mortar activated by sodium sulphate (Na2SO4º. In this study, two types of steel slag, classified as fine steel slag (FSS) with particle sizes of 0.075mm and coarse steel slag (CSS) with particle sizes of 0.150 mm, were used for making alkali activated steel slag (AASS) mortar. Flow table test, compressive strength test, flexural strength test and UPV test were carried out by designing and producing AASS mortar cubes of (50 x 50 x 50) mm at 0, 10%, 20% and 30% replacement ratio and at 0.85% addition of Na2SO4. The results show that the AASS mortar with FSS possess a relatively good strength in AASS mortar. AASS mortar with FSS which is relatively finer shows a higher compressive strength than CSS up to 38.0% with replacement ratio from 10% to 30%. This study provided the further investigation on the combined influence of replacement ratio and particle size of SS in the properties of fresh and hardened AASS.

The article presents the method of identifying surface damage by measuring changes in resistance in graphitebased sensing skin. The research focused on analysis of conductivity anomalies caused by surface damage. Sensitivity maps obtained with Finite Element Method (FEM) in conjunction with the analytical damage model were used to build the coating evaluation algorithm. The experiment confirmed the ability of this method to identify a single elliptical-shape damage. Eight electrodes were enough to locate the damage that covered about 0.1‰ of the examined area. The proposed algorithm can prove useful in simple applications for surface condition monitoring. It can be implemented wherever it is possible to apply a thin layer of conductor to a non-conductive surface.