Nonlinear Induction Research Articles

Tensor Product Alternatives for Nonlinear Field-Oriented Control of Induction Machines

The paper presents a nonlinear field-oriented control technique based on the tensor product representation of the nonlinear induction machine model and the solvability of linear matrix inequalities. The nonlinear model has 32 quasi linear parameter-varying equivalent variants, and it is shown that only half of the models result in feasible controller. Two control goals are realized: torque control and speed control. The controller is a nonlinear state feedback controller completed by integral action. A new block diagram is investigated for speed control. The controller gains are designed by the solution of linear matrix inequalities to solve the Lyapunov inequality to obtain a stable and fast response and constraints on the control signal. The presented methods are verified and compared by simulations.

Linear-Matrix-Inequality-Based Controller and Observer Design for Induction Machine

The modeling and drive control of electric machines are still actively researched scientific topics. Most of the existing models contain parameters that have no physical content or cannot be measured at all. For this reason, the use of observers in modern drive control algorithms is necessary. The main goal of this paper is to present the mathematical formalism of a linear matrix inequality (LMI)-based controller-observer design for a tensor product (TP) transformation-based model, including its implementation in a simulation environment. Based solely upon simulation results, the designed observer can provide a stable and accurate state space variable, regardless of the highly nonlinear induction machine model.

Nonlinear Induction of Acoustic Perturbations by Alfven Waves in Partially Ionized Plasma

Nonlinear Induction of Acoustic Perturbations by Alfven Waves in Partially Ionized Plasma

Finite-time command filter-based adaptive fuzzy tracking control for stochastic nonlinear induction motors systems with unknown backlash-like hysteresis

In this article, an adaptive fuzzy control method is proposed for induction motors (IMs) drive systems with unknown backlash-like hysteresis. First, the stochastic nonlinear functions existed in the IMs drive systems are resolved by invoking fuzzy logic systems. Then, a finite-time command filter technique is exploited to overcome the obstacle of “explosion of complexity” emerged in the classical backstepping procedure during the controller design process. Meanwhile, the effect of the filter errors generated by command filters is decreased by utilizing corresponding error compensating mechanism. To cope with the influence of backlash-like hysteresis input, an auxiliary system is constructed, in which the output signal is applied to compensate the effect of the hysteresis. The finite-time control technology is adopted to accelerate the response speed of the system and reduce the tracking error, and the stochastic disturbance and backlash-like hysteresis are considered to improve control accuracy. It’s shown that the tracking error can converge to a small neighborhood around the origin in finite-time under the constructed controller. Finally, the availability of the presented approach is validated through simulation results.

Investigations of non-linear induction motor model using the Gudermannian neural networks

This study aims to solve the non-linear fifth-order induction motor model (FO-IMM) using the Gudermannian neural networks (GNN) along with the optimization procedures of global search as a genetic algorithm together with the quick local search process as active-set technique (GNN-GA-AST). The GNN are executed to discretize the non-linear FO-IMM to prompt the fitness function in the procedure of mean square error. The exactness of the GNN-GA-AST is observed by comparing the obtained results with the reference results. The numerical performances of the stochastic GNN-GA-AST are provided to tackle three different variants based on the non-linear FO-IMM to authenticate the consistency, significance and efficacy of the designed stochastic GNN-GA-AST. Additionally, statistical illustrations are available to authenticate the precision, accuracy and convergence of the designed stochastic GNN-GA-AST.

Soliton-Like Spherical Symmetric Solutions to the Electromagnetic and Scalar Nonlinear Induction Field Equations in the General Relativity Theory

In this paper, we have used the static spherical symmetric metric. The parameter of the nonlinearity fields is included in the arbitrary function characterizing the interaction between the electromagnetic and scalar fields. Taking into account the own gravitational field of elementary particles, we have obtained exact static spherical symmetric solutions to the electromagnetic and scalar field equations of nonlinear induction. Considering all forms of the solution of Liouville equation, we proved that the metric functions are regular with localized energy density. Moreover, the total energy of the nonlinear induction fields is bounded and the total charge of the elementary particles has a finite value (soliton-like). In the flat space-time, soliton-like solutions exist.

Model calibration strategy for energy-efficient operation of induction machines

This contribution describes a novel calibration procedure for nonlinear induction machine models. It is based on measurements of the electrical quantities and the rotational speed, and uses additional measurements of the torque. Since the method uses quasi steady-state measurements, the calculations required for the model calibration can be performed with low computational costs in the frequency domain. Compared to the scientific state of the art, higher harmonics are taken into account in addition to the fundamental wave. The main goal of the parametrized model is to accurately capture the behavior of the induction machine in the vicinity of maximum efficiency operating points. Thus, the calibration strategy is tailored to these important operating points and allows to obtain a very high accuracy with a rather simple model. The proposed calibration procedure is verified by measurements on a test bench. It is shown that a high model accuracy can be achieved with the calibrated model.

Exact static spherical symmetric soliton-like solutions to the scalar and electromagnetic nonlinear induction field equations in general relativity

In this paper, we have obtained exact static spherical symmetric soliton-like solutions to the electromagnetic and scalar nonlinear induction field equations taking into account the own gravitational field of the elementary. The results show that the metric tensor functions are regular with localized energy density. Moreover, the total energy of the nonlinear induction fields is bounded and the total charge of elementary particles has a finite value. The importance of the own gravitational field of elementary particles and the role of the nonlinearity of fields in the determination of these solutions have been proved.

Existence of a weak solution to a nonlinear induction hardening problem with Leblond–Devaux model for a steel workpiece

In the present paper, we investigate a mathematical model for an induction hardening process of a steel workpiece. We describe the electromagnetic process by the eddy current equations, which are coupled with the energy balance in the workpiece via the heat equation and the kinetic phase transition. The nonlinearities of the system are caused by a nonlinear relation between the magnetic induction and the magnetic field, together with a nonlinear heat conduction and Joule heating. We propose a time discretization for the variational system, and perform some a priori estimates for discrete solutions. By aid of Rothe’s method and the theory of monotone operators, we show the convergence of the proposed scheme and the existence of a weak solution to the variational problems.

Modeling, Small-Signal Stability Analyzing and Implementing of an Inverter-based Distributed Generation with Feed-forwarded Model Predictive Controller

Nowadays the control and stability of DG systems are important topics that researchers in both academia and industry. Small and large signal analyses for stability studies on various systems have been done in papers and books. In this paper, first models of an inverter-based Distributed Generation (DG) subsystems are created. After the linearization, if required, the small-signal stability analysis of the DG which is controlled with a voltage and frequency control scheme based on the model predictive control (MPC) that has been used previously, is established. In this control scheme, load currents at the point of common coupling (PCC) of the DG are considered as disturbances and used as feed-forward signals. This technique enhances the performance of the DG control system in transient and steady-state conditions for a wide range of loads. The stability of the DG system under various loads (such as one phase load as imbalanced load, rectifier load as nonlinear load and induction motor load as dynamic load) is demonstrated by the eigenvalues trajectory. The sensitivity analysis and robustness assessment of the control scheme are also conducted and discussed. For more performance consideration, the DG system is simulated with MATLAB/SIMULINK software, implemented in the lab and later the suitable performance of the system is demonstrated by the simulation and experimental studies.

Dose and Dose Rate-Dependent Effects of Low-Dose Irradiation on Inflammatory Parameters in ApoE-Deficient and Wild Type Mice.

Anti-inflammatory low-dose therapy is well established, whereas the immunomodulatory impact of doses below 0.1 Gy is much less clear. In this study, we investigated dose, dose rate and time-dependent effects in a dose range of 0.005 to 2 Gy on immune parameters after whole body irradiation (IR) using a pro-inflammatory (ApoE−/−) and a wild type mouse model. Long-term effects on spleen function (proliferation, monocyte expression) were analyzed 3 months, and short-term effects on immune plasma parameters (IL6, IL10, IL12p70, KC, MCP1, INFγ, TGFβ, fibrinogen, sICAM, sVCAM, sE-selectin/CD62) were analyzed 1, 7 and 28 days after Co60 γ-irradiation (IR) at low dose rate (LDR, 0.001 Gy/day) and at high dose rate (HDR). In vitro measurements of murine monocyte (WEHI-274.1) adhesion and cytokine release (KC, MCP1, IL6, TGFβ) after low-dose IR (150 kV X-ray unit) of murine endothelial cell (EC) lines (H5V, mlEND1, bEND3) supplement the data. RT-PCR revealed significant reduction of Ki67 and CD68 expression in the spleen of ApoE−/− mice after 0.025 to 2 Gy exposure at HDR, but only after 2 Gy at LDR. Plasma levels in wild type mice, showed non-linear time-dependent induction of proinflammatory cytokines and reduction of TGFβ at doses as low as 0.005 Gy at both dose rates, whereas sICAM and fibrinogen levels changed in a dose rate-specific manner. In ApoE−/− mice, levels of sICAM increased and fibrinogen decreased at both dose rates, whereas TGFβ increased mainly at HDR. Non-irradiated plasma samples revealed significant age-related enhancement of cytokines and adhesion molecules except for sICAM. In vitro data indicate that endothelial cells may contribute to systemic IR effects and confirm changes of adhesion properties suggested by altered sICAM plasma levels. The differential immunomodulatory effects shown here provide insights in inflammatory changes occurring at doses far below standard anti-inflammatory therapy and are of particular importance after diagnostic and chronic environmental exposures.

Power quality monitoring for a solar PV grid controlled system at non-linear induction drives load

This paper unveils the impact of non-linear induction motor drives on operation of transformer-less single-stage solar photovoltaic (SPV) grid tied inverter system. The system is controlled by an indirect type data-based maximum power point tracking (MPPT) technique. A fuzzy-logic controlled (FLC) dynamic voltage restorer (DVR) is operated coordinating two non-linear induction motor drives load: direct torque flux control (DTFC) and field-oriented control (FOC). Importantly, power quality (PQ) analysis for FOC induction motor drive is validated with DTFC induction motor drive. Results reveal mitigation of unbalanced voltage sag and voltage swell among the SPV converter, load and grid during transient conditions produced by fault. The effectiveness of FLC-DVR at FOC drive load is demonstrated over DTFC drive load and linear load for validation. It is worth mentioning that controlling action of FLC-DVR is implemented effectively at non-linear loads. As illustrated by IEEE-519/1547 standard, a reduction in total harmonic distortion (THD) and DC offset current is reported in grid voltage and current for accuracy. The proposed framework illustrates a comparative PQ study to justify satisfactory performance under varying environmental conditions.

High-Fidelity CFD Validation and Assessment of Ducted Propellers for Aircraft Propulsion

This paper presents validation and assessment of ducted propellers for aircraft propulsion. Numerical methods and simulation strategies are put forward, including steady/unsteady high-fidelity computational fluid dynamics (CFD) simulations and simpler momentum-based methods. The validation and comparisons of the methods are made using a ducted propeller proposed by NASA. Simulations are also performed and analyzed at extended advance ratios, blade pitch setting, and cross-wind angles. Comparisons are also made with open propeller counterparts. The ducted propeller shows superior performance over its unducted counterpart in hover and at low advance ratios. The major thrust gain is identified from the combination of duct leading-edge suction and the higher pressure at the diffuser exit. The propeller is off-loaded due to the higher inflow velocities. The ducted propeller is also shown to have less intrusive wake features at low axial speeds. However, as the advance ratio increases, the duct thrust contribution becomes negative and the ducted propeller becomes deficient, due to growing high-pressure areas at the leading edge. At cross-wind, high-fidelity CFD simulations offer accurate aerodynamic loads predictions despite the complex flow features. The duct surface separation is found to be delayed due to the propeller suction, while the propeller is shown shielded by the duct, thereby suffering less from the unbalanced inflow velocities. Decomposition of induced velocities by each part is carried out and presented. A large, nonlinear extra induction component, due to mutual interactions of the duct and the propeller, is observed and found favorable for the performance augmentation.

MATHEMATICAL MODEL OF THE ADAPTABLE DISCHARGE CONTROL SYSTEM IN A TOKAMAK WITH AN IRON CORE

The previously developed adaptation models of the program regime used the so-called “local” adaptation model, i.e. when the correction of the control currents was carried out at each moment of time regardless of their change at other times. The main element was that the adaptation algorithms used were linear, i.e. are based on the linearization of the Kirchhoff system of equations describing the evolution of the control currents during the discharge. In this paper, an algorithm for “global” adaptation of control currents is proposed. It is based on a mathematical model for controlling the discharge in an iron-core tokamak, taking into account the nonlinear behavior of a ferromagnetic. In this model, the evolution of currents is described by the Kirchhoff equations with nonlinear mutual induction coefficients, and the restrictions on the control currents, voltages, and the equilibrium and stability conditions for the plasma are included in the corresponding discrepancy functional. To find the discharge scenario, the optimal control problem is formulated and solved. The algorithm of “global” adaptation consists in the fact that information about the previous discharges is included in the minimized functional, and then the problem of optimal control is solved and a new program scenario of the discharge and the corresponding control currents and voltages are found. As a result, the model of adaptation of the program regime, first, is nonlinear, i.e. nonlinearized Kirchhoff equations are used to describe the evolution of the control currents, and, secondly, the “global” one, since the correction of all currents is carried out interdependently and consistently during the entire discharge scenario. This approach allows us to redistribute the currents in advance in the critical situation (for example, additional heating) and provide the required program regime. This is especially important in an iron-core tokamak, when the connections between the control currents become highly nonlinear. In this work, using the example of the problem of additional heating for the T-15 tokamak, the work of the “global” adaptation algorithm is demonstrated.

A harmonic vibration suppression approach in nonlinear induction motors

A harmonic vibration suppression approach in nonlinear induction motors

Fully discrete T‐ψ finite element method to solve a nonlinear induction hardening problem

AbstractWe study an induction hardening model described by Maxwell's equations coupled with a heat equation. The magnetic induction field is assumed a nonlinear constitutional relation and the electric conductivity is temperature‐dependent. The T‐ψ method is to transform Maxwell's equations to the vector–scalar potential formulations and to solve the potentials by means of the finite element method. In this article, we present a fully discrete T‐ψ finite element scheme for this nonlinear coupled problem and discuss its solvability. We prove that the discrete solution converges to a weak solution of the continuous problem. Finally, we conclude with two numerical experiments for the coupled system.

Fault tolerant sliding mode intelligent control based on fault hiding for a nonlinear induction furnace system

In this article, the design of a fault tolerant controller for an induction furnace is presented. The fault studied was that of an actuator fault in the furnace. The design is comprised of a fault detection and identification (FDI) unit as well as a reconfiguration block. The induction furnace is modeled using Radial Basis Function (RBF) neural networks so that when an actuator fault happens, the FDI block detects and estimates the magnitude of the fault that occurred. Then based on a fault hiding strategy, the reconfiguration mechanism is activated to accommodate the destructive effects of the fault in a way that from the controller’s point of view the actuator fault is hidden. Utilization of the RBF neural networks model in the system also gives training ability to the system and raises its intelligence. In order to make the system robust against uncertainties caused by the fault, a sliding mode scheme is implemented as well. Using Lyapunov’s stability approach, the stability of the proposed method is verified. Finally, the simulation result of this method on the induction furnace system validates the effectiveness of the proposed algorithm in the presence of an actuator fault.

Ca2+ channel dynamics explain the nonlinear neuroplasticity induction by cathodal transcranial direct current stimulation over the primary motor cortex

Transcranial direct current stimulation (tDCS) induces polarity-dependent neuroplasticity: with conventional protocols, anodal tDCS results in excitability enhancement while cathodal stimulation reduces excitability. However, partially non-linear responses are observed with increased stimulation intensity and/or duration. Cathodal tDCS with 2 mA for 20 min reverses the excitability-diminishing plasticity induced by stimulation with 1 mA into excitation, while cathodal tDCS with 3 mA again results in excitability diminution. Since tDCS generates NMDA receptor-dependent neuroplasticity, such non-linearity could be explained by different levels of calcium concentration changes, which have been demonstrated in animal models to control for the directionality of plasticity. In this study, we tested the calcium dependency of non-linear cortical plasticity induced by cathodal tDCS in human subjects in a placebo controlled, double-blind and randomized design. The calcium channel blocker flunarizine was applied in low (2.5 mg), medium (5 mg) or high (10 mg) dosages before 20 min cathodal motor cortex tDCS with 3 mA in 12 young healthy subjects. After-effects of stimulation were monitored with TMS-induced motor evoked potentials (MEPs) until 2 h after stimulation. The results show that motor cortical excitability-diminishing after-effects of stimulation were unchanged, diminished, or converted to excitability enhancement with low, medium and high dosages of flunarizine. These results suggest a calcium-dependency of the directionality of tDCS-induced neuroplasticity, which may have relevant implications for future basic and clinical research.

P276 Ca2+ channel dynamics explain the nonlinear neuroplasticity induction by cathodal transcranial direct current stimulation over the primary motor cortex

P276 Ca2+ channel dynamics explain the nonlinear neuroplasticity induction by cathodal transcranial direct current stimulation over the primary motor cortex

Modeling Nonlinear Steady-State Induction Heating Processes

In this article, an efficient simulation strategy for a fully coupled nonlinear magnetic-thermal problem is presented. The solution-dependent magnetic subproblem is solved with a harmonic balancing scheme, with the main focus on the correct choice of the material model (magnetization curve). To further increase the computational efficiency, a non-conforming interface approach is used, based on the jump operators and penalty terms. This method drastically decreases the meshing time because different mesh sizes can be combined without taking care of element distortions in transition layers between fine and coarse parts of the mesh.