Varying Time Constants Research Articles

Fuzzy Improvement on Luenberger Observer Based Induction Motor Parameters Estimation for High Performances Sensorless Drive

In this paper we present a new improved sensorless vector control of induction motor based on an improved adaptive Luenberger observer. The proposed observer is designed to estimate both speed and motor parameters from measured stator currents, stator voltages and estimated rotor fluxes. The proposed sensorless drive has for purpose to compensate at the same time both stator resistance and rotor time constant inverse variation, which change during operation. Indeed, in the proposed adaptive Luenberger observer, a Fuzzy Logic Controller will be adopted as an adaptation mechanism. The proposed observer stability is proved by the Lyapunov’s theorem and its feasibility is verified by series of experimental tests. The relevant results and the effectiveness of the improved system are clearly shown through obtained experimental results with an induction motor of 1 kW driven by dSPACE system.

Offline method for experimental identification of load‐dependentsaturation of induction motor taking into account variation of inverse rotortime constant

Accurate knowledge of induction machine parameters has a direct impact on the overall performance of field-oriented control strategies. In the case of rotor flux oriented control, parameter mismatch causes a discrepancy in the estimated rotor flux position and amplitude. Magnetising inductance is one of the parameters whose detuning has a direct impact on the setpoints of the control loops and estimation of hardly or non-measurable quantities. Conventional iron saturation, which can be obtained by a standard no-load test, is not the only type of saturation occurring in the machine. Depending on the rotor design, the magnetising inductance and the rotor leakage inductance may also strongly saturate as a function of load and, thus, rotor current. Based on the authors’ previous work, a new, improved experimental method for identifying the load-dependent saturation of induction motor, which takes into account variation of the inverse rotor time constant, is proposed. Experimental results conducted on 12 kW motor show improved static and dynamic behaviour of the drive compared to the constant parameter model.

Fractional Order PID Parameter Tuning for Solar Collector System Based on Frequency Domain Analysis

The control aim of parabolic distributed solar collector (PDSC) is to make the heat generated follow the expected reference value when the solar radiation varies unevenly. This article proposes a control strategy based on fractional-order PID (FOPID) to achieve control objectives. Four non-linear constraints and an objective function of the controller are proposed based on the frequency domain. Most studies regard the constraint measuring stability as the objective function, while the real difficulty for the control system design should be how to obtain better robustness. Therefore, this article determines five parameters of FOPID by selecting the constraint measuring robustness as the objective function based on Particle swarm optimization (PSO). Besides, three non-parametric statistical tests, including Friedman ranks, Friedman Aligned ranks and Quade ranks, have been adopted to compare PSO with other evolutionary algorithms to demonstrate its advantage. Finally, the superiority of proposed strategy to previous design is demonstrated by the simulation studies on a PDSC in terms of the control performance of step response, static gain variation, time constant variation, high frequency noise and output interference.

Classroom activity to visually show variation of RC time constant in an operating circuit

An RC series circuit, incorporating readily-available components, along with interactive activities for students are discussed in order to demonstrate how the RC time constant varies with changes in resistance and/or capacitance. The circuit uses a flashing Neon bulb to visually monitor variations of the RC time constant. With the aid of a projection camera, the circuit described is ideal for use in classroom settings and requires only 1–3 min of set-up time.

Ultrafast dynamics of pure many-body effect and its competition with bandgap widening via electron–phonon coupling in PbTe thin films

Bandgap renormalization (BGR), or bandgap narrowing effect, is one of the many-body effects predicted by many-body theory in semiconductor physics. However, pure BGR effect has never been observed experimentally although the mixed effect of BGR with lattice-heating induced bandgap narrowing was reported in GaAs and CdTe semiconductors. PbTe has a positive temperature coefficient of bandgap. Its lattice-heating induced bandgap narrowing can be eliminated so that the pure BGR effect is possibly observed. However, that has never been reported so far because the BGR effect is weak in PbTe due to its huge dielectric screening. We study the ultrafast dynamics of photo-excited carriers in PbTe films using near-infrared femtosecond-resolved transient differential transmission (TDT) spectroscopy. A complex oscillation-like damped decay dynamics is observed. A negative dip, a fingerprint signature of BGR effect, occurs immediately after the thermalization process of the photo-excited carriers. As such, we have observed a pure BGR effect in PbTe for the first time, strongly supporting the many-body theory. Meanwhile, we have also observed a dynamic transition from a transient absorption enhancement to absorption saturation, revealing the emergence of a slow lattice-heating induced bandgap widening via carrier-phonon couplings. Based on a two-temperature model, a simulation computation is carried out, supporting the lattice-heating induced bandgap widening leads to the dynamic transition. A phenomenological dynamic model is developed, including three dynamic components: the thermalization of the photo-excited carriers, recombination of the thermalized carriers and lattice-heating induced bandgap widening, and used to best fit the excitation-power dependent TDT dynamics. Time constants and strengths of the three dynamic components are obtained for different excitation powers. Time constant variation with the excitation power reveals different roles of the carrier–carrier and carrier-phonon scattering in the thermalizing process, as well as of free carrier and exciton recombination in the decaying process of hot carriers.

Harmonic Phasor Estimator for P-Class Phasor Measurement Units

Fast harmonic phasor measurements are very useful in power system protection applications, e.g., high-impedance fault location and intelligent method-based islanding detection. To address this problem, a novel harmonic phasor estimator is proposed in this paper, especially for P-class phasor measurement units (PMUs). The exponential functions are used to model the decaying dc (ddc) component, and the optimal time constant (TC) set for the ddc model is searched based on an enumeration method. In addition, the dynamic harmonic phasors are modeled based on the Shannon sampling theorem. As a result, a filter bank is designed for harmonic phasor and frequency estimations. The rate of change of frequency (ROCOF) of the harmonic is estimated based on a second-order fitting method. The response time of the proposed method for harmonic phasor estimation is always no longer than 40 ms. Simulation test results indicate that the proposed method is more accurate than the Taylor–Fourier transform (TFT) under ddc offset and frequency deviation conditions. In particular, the proposed method is more robust to ddc’s TC variations. An experimental test is implemented to demonstrate the advantages of the proposed method.

Dynamics and Control of Liquid Level in Annular Conical Tank Process: Modelling and Experimental Validation

Objectives: The present work has been carried out to prove the superiority of IMC based PID control strategy over the conventional PID, based on simulation studies and experimental validation on an annular conical tank liquid level nonlinear process. Methods/Statistical Analysis: First principles based Mathematical Model of an annular conical tank liquid level nonlinear process has been developed based on the mass balances and outlet flow hydraulic characteristics. Linearization of the nonlinear model at a specific steady-state operating point led to the theoretical development of state-space and standard first order transfer function models. Open loop and closed loop experimental studies on a computer controlled physical setup were performed to identify the parameters of a FOPDT Model with variable gain and time constant. IMC based PID controller was designed and compared to the conventional PID controller. Findings: The variation in process parameters was attributed to two factors: (a) the variation in annular cross sectional area of the conical tank at different levels, and (b) the variation in outlet flow resistance. The IMC based PID controller has been shown to exhibit superior performance in terms of quantitative performance indices such as ISE, IAE, ITAE, rise time, settling time and percentage overshoot, at four different steady-states. Application/Improvements: Study of Modelling of annular conical tank process and a systematic methodology of process system identification from experimental setup have been reported. The advantages of IMC based PID controller design over the conventional PID tuning method has been experimentally verified. Keywords: Annular Flow Conical tank process, FOPDT model, System Identification, PID controller tuning, IMC based PID.

A Study on Use of Hybrid Energy Storage System Along With Variable Filter Time Constant to Smooth DC Power Fluctuation in Microgrid

Currently, using hybrid energy storage system composed of battery and supercapacitor to stabilize DC bus power fluctuation is a hot issue. In low-pass filtering control strategy to suppress the power fluctuation of DC bus, the filtering time constant is fixed, so there are problems such as poor load power fluctuation smoothing effect and over-charge and over-discharge of the battery. In this paper, a two-stage low-pass filter control strategy with variable filter time constant is designed. Firstly, the strategy builds a multi-objective function with minimum load slow target power and DC bus power difference. Using the Improved Particle Swarm Optimisation (IPSO) with compensating coefficient of inertia weight factor to solve the optimal output power by a hybrid energy storage system, and dynamically adjust the first-level filtering time constant, in order to reduce the load power change causing the fluctuation of the DC bus power; secondly, according to the charging state of the supercapacitor and the battery, the fuzzy control method is adapted to dynamically adjust the second-order filtering time constant to optimize the power distribution of the battery and the supercapacitor. The experimental results show that the control strategy can effectively reduce the power fluctuation of DC bus by about 15%, and avoid the over limit phenomenon of the battery state of charge, which has a good prospect of engineering application.

Photosensitive Glass-Ceramics for Heterogeneous Integration

The push for heterogeneous integration requires very unique material properties with respect to processing, material constants, and integration capabilities with other materials (such as copper, II...

Coupling of living cells with external electrical stimulation: a computational study

The coupling of external electric field (E-field) with living cells results in a profound effect on their metabolic activities. In order to develop a fundamental understanding of such couplings, four different electrical equivalent circuits for a living cell have been considered. As an estimate of response time of single cell in E-field, the time constant of cell and, subsequently, the influences of cell size, cytoplasmic and nucleoplasmic resistances, as well as cell and nuclear membrane capacitances, on the time constant have been analytically computed. Such computational analysis was performed by considering (a) cell membrane as leaky dielectric and (b) both the cell and nuclear membranes as leaky dielectrics, which suggest similar values (1.5 µs–5 µs), owing to the high value of nuclear membrane resistance. The variation of time constants with various electrophysical parameters of cells, such as cell size, cytoplasm and nucleoplasm resistances, as well as cell and nuclear membrane capacitances and resistances, suggests similar characteristics for both (a) and (b). To validate the proposed electric equivalent models, an analytical study for the well-known electroporation phenomenon has been carried out using similar models and the results have been observed to be consistent with the experimentally observed values.

General robustness analysis and robust fractional‐order PD controller design for fractional‐order plants

Most of the existing controller tuning methods are based on accurate system model and sensitive to some inevitable uncertainties and unmeasurable disturbance. Aiming at this problem, a thorough robustness analysis on a typical kind of fractional-order (FO) delay system has been made in this study. A kind of robust FO proportional and derivative controller is proposed based on phase and gain margins. The tuning methods are demonstrated under different circumstances, namely there is gain variation, time constant variation, order variation or even multiple parameters variations in system transfer function. Simulation results show that the closed-loop control system with the proposed controller can achieve both robustness and satisfactory dynamic performance, and outperform the conventional proportional-integral-derivative controller in all cases.

Design of PID controller for automatic voltage regulator system using Ant Lion Optimizer

PurposeNow days, various techniques are used for controlling the plants. New ideas are evolving day by day to get better-quality control for various industrial processes to produce high-quality products. Currently, the focus of this research is being emphasized on application of nature-inspired algorithms in control systems. The purpose of this paper is to apply a nature-inspired algorithm called Ant Lion Optimizer (ALO) for the design of proportional-integrator-derivative (PID) controller for an automatic voltage regulator (AVR) system.Design/methodology/approachFor the design of the PID controller, the ALO algorithm is considered as a designing tool for obtaining the optimal values of the controller parameter. All the simulations are carried out in Simulink/MATLAB environment. A comparative study is carried out with some modern nature-inspired algorithm to describe the advantages of this tuning method.FindingsThe proposed method has superiority value in transient and frequency domain analysis than the other published heuristic optimization algorithms. The presented approach has almost no variation in transient response when varying time constants of the system parameter, such as exciter, generator, amplifier and sensor from −50 per cent to +50 per cent. In addition, the close loop system is robust against any disturbances such as input–output disturbances and parametric uncertainty, as the sensitivity values are nearly equal to one.Originality/valueThe proposed method presents the design and performance analysis of proportional integral derivate (PID) controller for an AVR system using the recently proposed ALO.

Benchmark Challenge: a robust fractional order control autotuner for the Refrigeration Systems based on Vapor Compression

This paper proposes fractional order autotuner controller for the benchmark refrigeration system. The method is an extension of a previously presented autotuning principle and produces a robust fractional order PI controller to gain variations. Fractional order PI controllers are generalizations of the integer order PI controllers, which have a supplementary parameter that is usually used to enhance the robustness of the closed loop system. The method is not restricted to robustness to gain variations and can be adapted to obtain robust fractional order controllers to time delay or time constant variations, for example. The autotuning method presented in this paper has several advantages such as the need for a single sine test to be applied to the process to extract the necessary information and the elimination of complex nonlinear equations in the tuning procedure for fractional order controllers. The results obtained on the benchmark system indicate the method has high potential for real-life applications.

Discrete Data AGC of Hydrothermal Systems Under Varying Turbine Time Constants Along With the Power System Loading Conditions

The paper deals with the discrete data automatic generation control (AGC) of two area hydrothermal power system operating at different loading conditions. The power system load varies considerably throughout the day and accordingly, thermal and hydropower systems are scheduled to operate at different loading conditions. It is found that steam as well as hydro turbine time constants vary as the power system loading varies. In earlier AGC studies, these parameters are considered to be constant, irrespective of power system loadings. This paper studies the dynamic performance of hydrothermal power system considering the variation of these turbine time constants along with the nominal loading of power system. The studies have been conducted for linear as well as nonlinear models of speed governor and hydroturbine models recommended by the IEEE committee. It is also discovered that conventional empirical formula-based hydraulic governor settings recommended by the IEEE working group are completely unacceptable for hydrothermal power system. A maiden attempt is made to optimize the hydraulic governor settings simultaneously along with the controller gains using metaheuristic algorithm. The comparison of system dynamic responses reveal that optimization-based hydrogovernor settings give the better dynamic performance in case of linear as well as nonlinear models of hydro system, and therefore are strongly recommended over the conventional settings. The paper also deals with the optimum selection of sampling periods for discrete data AGC operation of hydrothermal systems.

A two-stage robust-intelligent controller design for efficient LFC based on Kharitonov theorem and fuzzy logic

This paper proposes an efficient load frequency control (LFC) approach based on robust and intelligent methods. Practically speaking, proportional-integral (PI) controller is widely deployed in LFC structure. Basically, the parameters of PI controller are adjusted based on trial-and-error or classic control methods. In such manners, robust performance of PI controller cannot be guaranteed in disturbances including load changes or parameter variations. In this research, at the first stage, the gain values of PI controller are tuned in an offline manner based on Kharitonov theorem which strengthens the validity of the controller against the variations in time constants of turbine and governor. As another aspect of uncertainty, power system loading demand is changed ceaselessly. To accommodate such conditions, at the second stage, the initial gain values based on Kharitonov theorem are adapted in an online manner based on fuzzy logic approach. The fuzzy controller, as an aspect of intelligence, adapts the proportional and integral gains through appropriate membership functions in an online fashion. Frequency deviation and its derivative are selected as efficient input signals for the fuzzy controller. Detailed numerical studies are conducted to assess performance of the proposed approach. Results demonstrate a reliable frequency performance against different uncertainties.

Eddy Current Probe Identification and Analysis

This paper presents a new approach to the classical method for failure detection with eddy currents. In contrast to traditional methods of measuring reflected impedance on the probe circuit, this paper uses concepts of identification theory to find a transfer function that characterizes the dynamics of the measuring system by eddy currents. The transfer function represents the admittance of the input equivalent circuit. The estimated parameters of the transfer function were used to compute the inductive time constant of equivalent circuit of the metal specimen. The results of the time constant variation of the equivalent circuit of the sample were compared with the equivalent input impedance variation. A preliminary analysis is done in a simple case study, which has shown that the inductive time constant is more sensitive than the reflected impedance on the probe circuit, especially at low frequencies. Moreover, the estimated time constant is independent of the excitation frequency and mutual inductance.

Numerical and experimental validation of variation of power transformers’ thermal time constants with load factor

Thermal time constants (TTC) of a thermal dynamic model reflect the change rate of temperature, which are affected by many factors such as load current, oil temperature, etc. In this study, relative thermal time constants (RTTC) are introduced and formulated to describe the variation of thermal time constants with load current. It is verified through extensive case studies based on computational fluid dynamic (CFD) simulation and field measurements. Specific for CFD simulation, the polyhedral meshing was applied to mesh division of 3D model due to narrow part such as discs in transformer. The proposed relative thermal time constants can be integrated with dynamic thermal model to estimate the hot-spot temperature of transformers, especially in overload situations. Accuracy and adequacy metrics are used to quantify the accuracy of presented thermal model with proven thermal model.

Mechanisms of generation of membrane potential resonance in a neuron with multiple resonant ionic currents.

Neuronal membrane potential resonance (MPR) is associated with subthreshold and network oscillations. A number of voltage-gated ionic currents can contribute to the generation or amplification of MPR, but how the interaction of these currents with linear currents contributes to MPR is not well understood. We explored this in the pacemaker PD neurons of the crab pyloric network. The PD neuron MPR is sensitive to blockers of H- (IH) and calcium-currents (ICa). We used the impedance profile of the biological PD neuron, measured in voltage clamp, to constrain parameter values of a conductance-based model using a genetic algorithm and obtained many optimal parameter combinations. Unlike most cases of MPR, in these optimal models, the values of resonant- (fres) and phasonant- (fϕ = 0) frequencies were almost identical. Taking advantage of this fact, we linked the peak phase of ionic currents to their amplitude, in order to provide a mechanistic explanation the dependence of MPR on the ICa gating variable time constants. Additionally, we found that distinct pairwise correlations between ICa parameters contributed to the maintenance of fres and resonance power (QZ). Measurements of the PD neuron MPR at more hyperpolarized voltages resulted in a reduction of fres but no change in QZ. Constraining the optimal models using these data unmasked a positive correlation between the maximal conductances of IH and ICa. Thus, although IH is not necessary for MPR in this neuron type, it contributes indirectly by constraining the parameters of ICa.

Time constant optimization of solar irradiance absolute radiometer

We experimentally evaluate and optimize the time constant of solar irradiance absolute radiometer (SIAR). The systemic error introduced by variable time constant is studied by a finite element method. The results shown that, with a classic time constant of 30 s for SIAR, the systemic errors are 0.06% in the midday and 0.275% in the morning and afternoon. The uncertainty level which can be considered negligible for SIAR is also investigated, and it is suggested that the uncertainty level has to be less than 0.02%. Then, combining the requirement of international comparison with these two conclusions, we conclude that the suitable time constant for SIAR is 20 s.1

Effects of concentration and vendor specific composition of formalin on postmortem MRI of the human brain.

Formalin fixation prevents tissue autolysis by crosslinking proteins and changes tissue microstructure and MRI signal characteristics. Previous studies showed high variations in MR relaxation time constants of formalin fixed brain tissue, which has been attributed to the use of different formalin concentrations. Our investigations confirmed the influence of formalin concentration on relaxation times and unexpectedly revealed an influence of vendor specific formalin composition, which has not been investigated so far. We systematically analyzed relaxation times of human brain tissue fixed with 4% and 10% formalin compared with unfixed condition at 3 Tesla MRI. Furthermore, we assessed relaxation times of nine formalin solutions from different vendors and performed comparisons of their magnetic susceptibility by SQUID (superconducting quantum interference device) magnetometry. Tissue relaxation times decreased approximately twice as fast using 10% than in 4% formalin fixation. The vendor specific composition of the formalin solutions and concentration dependent paramagnetic effects showed a substantial contribution to differences in relaxation times of formalin. Our study demonstrates that differences of the formalin composition have substantial effects on MRI signal characteristics after fixation, which can explain the divergence of reported relaxation times beyond the effect of differences in formalin concentration. Magn Reson Med 79:1111-1115, 2018. © 2017 International Society for Magnetic Resonance in Medicine.