Order Dynamic Model Research Articles

Spin angular momentum induced by optical quasi-phonons activated in birefringent uniaxial crystals

The present report formally establishes the expression of the angular momentum of the quasi-phonons induced by linearly polarized light. The transferred mechanical torque due to phonons is then determined from the spin angular momentum and is shown to be measurable from Raman scattering experiments. To investigate this, the electric field due the excited dipoles and the associated macroscopic dielectric polarization vectors were first calculated using a lattice dynamical model in order to derive in a second step the analytical expression of the angular momentum density arising from the inelastic light scattering by quasi-phonons. The numerical results of the calculated angle dependent mode electric fields and the induced spin angular moments as well as the transferred torques were analyzed with regard to some typical behaviors of the interacting modes and it is shown that the fluctuations of the effective charges is their main origin.

A novel inverse dynamic model for a magnetorheological damper based on network inversion

Semi-active suspensions based on magnetorheological (MR) dampers are receiving significant attention, especially for control of vibration isolation systems. The nonlinear hysteretic behavior of MR dampers can cause serious problems in controlled systems, such as instability and loss of robustness. Most of the developed controllers determine the desired damping forces which should be produced by the MR damper. Nevertheless, the MR damper behavior can only be controlled in terms of the applied current (or voltage). In addition to this, it is necessary to develop an adequate inverse dynamic model in order to calculate the command current (or voltage) for the MR damper to generate the desired forces as close as possible to the optimal ones. Due to MR dampers being highly nonlinear devices, the inverse dynamics model is difficult to obtain. In this paper, a novel inverse MR damper model based on a network inversion is presented to estimate the necessary current (or voltage) such that the desired force is exerted by the MR damper. The proposed inverse model is validated by carrying out experimental tests. In addition, a comparison of simulated tests with other damper controllers is also presented. Results show the effectiveness of the network inversion for inverse modeling of an MR damper. Thus, the proposed inverse model can act as a damper controller to generate the command current (or voltage) to track the desired damping force.

A note on applications of time-domain solution of Cole permittivity models

The complex dielectric permittivity is an important parameter for characterization of electrical properties of dielectric materials. Experimental studies demonstrated that Cole models of dielectric permittivity can provide a better fitting to the experimental data because of allowing for fractional-order frequency dependence. This study aims to investigate physical interpretation of time domain solutions of Cole permittivity models. For this purpose, impulse responses of Cole-Cole model and Davidson-Cole model are expressed in Mittag-Leffler function form by using inverse Laplace transform. The impulse responses of these models are decomposed into impulsive and dispersive components, and the relations of these components with relaxation mechanism of dielectric materials are discussed. By considering impulse response solution of Cole-Cole models, a fractional order dynamic capacitance model is introduced for time domain equivalent circuit modeling of dielectric materials. Moreover, transient properties of electromagnetic wave penetration to dielectric materials are analyzed according to impulse response solution of Cole-Cole model. To illustrate applications of proposed time domain permittivity solutions, the Cole-Cole model of ethyl-acetate liquids was also studied and results are presented.

SMAD transcription factors are altered in cell models of HD and regulate HTT expression

Transcriptional dysregulation is observable in multiple animal and cell models of Huntington's disease, as well as in human blood and post-mortem caudate. This contributes to HD pathogenesis, although the exact mechanism by which this occurs is unknown. We therefore utilised a dynamic model in order to determine the differential effect of growth factor stimulation on gene expression, to highlight potential alterations in kinase signalling pathways that may be in part responsible for the transcriptional dysregulation observed in HD, and which may reveal new therapeutic targets. We demonstrate that cells expressing mutant huntingtin have a dysregulated transcriptional response to epidermal growth factor stimulation, and identify the transforming growth factor-beta pathway as a novel signalling pathway of interest that may regulate the expression of the Huntingtin (HTT) gene itself. The dysregulation of HTT expression may contribute to the altered transcriptional phenotype observed in HD.

Decoding gripping force based on local field potentials recorded from subthalamic nucleus in humans

The basal ganglia are known to be involved in the planning, execution and control of gripping force and movement vigour. Here we aim to define the nature of the basal ganglia control signal for force and to decode gripping force based on local field potential (LFP) activities recorded from the subthalamic nucleus (STN) in patients with deep brain stimulation (DBS) electrodes. We found that STN LFP activities in the gamma (55-90 Hz) and beta (13-30m Hz) bands were most informative about gripping force, and that a first order dynamic linear model with these STN LFP features as inputs can be used to decode the temporal profile of gripping force. Our results enhance the understanding of how the basal ganglia control gripping force, and also suggest that deep brain LFPs could potentially be used to decode movement parameters related to force and movement vigour for the development of advanced human-machine interfaces.

Measurement-Based Hybrid Approach for Ringdown Analysis of Power Systems

System identification methods have been widely used for the study of low frequency electromechanical oscillations and the development of low order dynamic models. This paper introduces a hybrid frequency/time-domain approach to estimate the dominant modes contained in ringdown responses of power systems. Practical issues and solutions encountered in the application of the hybrid method are discussed. The performance of the proposed technique is evaluated by applying the Monte Carlo method to synthetic signals and simulated responses from a large-scale power system, as well as to measurements recorded in a microgrid laboratory test facility. Results in all cases proved to be very accurate, verifying the robustness of the proposed method.

Hierarchical Model Predictive Control of independent systems with joint constraints

This paper describes a hierarchical scheme for the control of independent stable systems subject to joint constraints. At the higher layer of the control structure reduced order dynamic models are used to minimize an economic cost function by adopting a long sampling time, while at the lower layer independent shrinking horizon MPC controllers working at a faster rate are designed for the original models to guarantee stability and convergence. A novel model reduction procedure is developed and simulation results are reported to witness the potentialities of the approach.

Dynamics of the interaction between the rotor and the induction zone

Traditionally met masts are used for power and load verifications. They are normally placed 2-4 rotor diameters ahead of the turbine. However in complex terrain this can lead to complex analysis of the effect of the terrain on the flow field. A nacelle mounted lidar can provide a better tool for wind field measurements in all terrains. Provided that the measurement is close enough to the rotor disc, the uncertainty in the flow field measurement can be reduced significantly. Therefore any complex terrain calibration and changes in the wind direction can be avoided. However, close distance lidar measurements are affected by the presence of the wind turbine, due to its induction zone. In this work, the dynamic coupling between changes in the wind turbine operating point and the velocities inside the induction zone is studied. Reynolds-Averaged Navier-Stokes (RANS) simulations are used to investigate this interaction. Thereafter, system identification is used to fit first order dynamic models to the simulation results. The parameters of the model are given for the turbine induction zone. These results possibly reduce the uncertainty in lidar measurements, arising from wind turbine blockage.

Numerical behavior of a fractional order dynamical model of RNA silencing

A class of fractional-order differential models of RNA silencing with memory is presented in this paper. We also carry out a detailed analysis on the stability of equilibrium and we show that the model established in this paper possesses non-negative solutions. Numerical solutions are obtained using a predictor-corrector method to handle the fractional derivatives. The fractional derivatives are described in the Caputo sense. Numerical simulations are presented to illustrate the results. Also, the numerical simulations show that, modeling the phenomena of RNA silencing by fractional ordinary differential equations (FODE) has more advantages than classical integer-order modeling.

Analysis and Applicability of Heffron–Phillips Model

In this paper, a non-linear 7th order dynamic model and a linearized 3rd order dynamic model of a synchronous generator connected to an infinite bus are presented and compared in details. Parameters and equations of the both models are explained and summarized. They represent a useful starting point for work in areas of synchronous generators’ construction, analysis, control systems design and synthesis. Novelty of this work represents a detailed research of applicability of the linearized model in an entire operating range. Established theoretical conclusions were confirmed with numerical results. Restrictions of utilizing the linearized model are presented. On a basis of the analysis for the synchronous generators of different power, their applicability with feasibility and accuracy was evaluated by certain objective criteria.DOI: http://dx.doi.org/10.5755/j01.eie.22.4.15905

Design of Nonlinear Synergetic Controller for Transient Stabilization Enhancement of DFIG in Multimachine Wind Power Systems

In this paper, an adaptive nonlinear controller for transient stabilization and voltage regulation of wind power systems based Double Fed Induction Generator (DFIG) in multimachine environment is described using a classical third order dynamical model of the DFIG. Estimation of non measurable time derivative signals (quadrature stator current component of the DFIG, mechanical input power, unknown transient open circuit time constant for direct axis) and an online computing technique for the operating points (e.g. power angle and its reference) are presented. The major advantage of the proposed control law is its robustness with respect to large disturbances, parameter variations and change of the operating point. Simulation results in the case of 4-machine power systems show the performance of the proposed control scheme and its heftiness properties.

Drogue dynamic model under bow wave in probe-and-drogue refueling

Probe-and-drogue refueling (PDR) is widely adopted owing to its simple requirement of equipment and flexibility, but it has an apparent drawback that the drogue position is susceptible to disturbances. There are three types of disturbances: atmospheric turbulence, trailing vortex of the tanker, and bow wave effect caused by the receiver. The former two disturbances are independent of the receiver, whereas the bow wave effect, which depends on the state of the receiver, greatly influences the docking within a close distance. As far as the authors know, little attention has been paid to the bow wave effect on docking control in existing literature. The existing literature related to the bow wave focuses on either qualitative static results obtained from experiments, or lookup tables based on computational fluid dynamics (CFD) analysis. These are inapplicable to the PDR docking controller design directly. This paper proposes a lower order dynamic model to describe drogue dynamics under the bow wave effect. The model consists of two components: one is a second-order transfer function matrix to describe the drogue dynamics, and the other is a nonlinear function vector to describe the bow wave effect model. A closed-loop simulation including the two components shows that the generated drogue dynamics are similar to those of a real experiment reported in an existing literature.

Fault diagnosis for a class of active suspension systems with dynamic actuators’ faults

In this paper, a new fault diagnosis and fault-tolerant control method for a class of active suspension systems with actuator faults is proposed. The considered actuators have uncertain dynamic characteristics, which are the electromagnetic actuators made up with a motor control system and a ball screw transmission mechanism. To detect such suspension system actuator faults, dynamic fault diagnosis observers are designed for the actuators to estimate the possible faults. The actuators are analyzed to first and second order dynamic models, respectively, whose output can be measured but the rate is non-measurable. Then, the fault diagnosis method is developed for these two kinds of models to obtain the fault information. Using the fault estimation and adaptive control technique, a robust fault-tolerant controller is constructed to guarantee the performance of the rail vehicles in the faulty case. Finally, using the parameters of a practical suspension system, a simulation study is conducted to show the effectiveness of the proposed method.

A Novel Dual Speed-Curve Optimization Based Approach for Energy-Saving Operation of High-Speed Trains

This paper studies the problem of high-speed train operation with special attention to minimizing the energy consumption. The performance characteristics of a high-speed train, including traction characteristic and regenerative braking, and the railway geographical conditions consisting of slope, curve, and tunnel parameters, are fully considered in the dynamic model in order to make it more effective and practical. A new optimal strategy for train operation is developed, and its novelty lies in the fact that it is the first time to optimize the actual speed curve using the method of dual speed curve optimization, which contains two processes of offline global optimization and online local optimization, thus leading to more energy saving as compared with most existing methods with only one-time optimization process. We utilize combination optimization techniques, in tandem with the speed codes and subsections, to solve the global optimization problem with a genetic algorithm. Predictive control is developed for local optimization to refine the global optimization in real time, more particularly, the train operation modes including traction, cruise, coast, and braking are switched on the base of the line slope information, from which a more energy-efficient speed trajectory is generated under the constraints of fixed time and distance. To verify the effectiveness of the proposed strategy, operation of CHR-3 on high-speed railway is tested. Through the comparison of energy consumption in two typical cases, it verifies that the proposed energy-saving strategy works better than that of single optimization strategy. At the same time, the actual speed deviation can be corrected in a timely manner with the proposed method.

Formulation and solutions of fractional continuously variable order mass–spring–damper systems controlled by viscoelastic and viscous–viscoelastic dampers

This article presents the formulation and a new approach to find analytic solutions for fractional continuously variable order dynamic models, namely, fractional continuously variable order mass–spring–damper systems. Here, we use the viscoelastic and viscous–viscoelastic dampers for describing the damping nature of the oscillating systems, where the order of fractional derivative varies continuously. Here, we handle the continuous changing nature of fractional order derivative for dynamic systems, which has not been studied yet. By successive recursive method, here we find the solution of fractional continuously variable order mass–spring–damper systems and then obtain closed-form solutions. We then present and discuss the solutions obtained in the cases with continuously variable order of damping for oscillator through graphical plots.

Dynamical balance optimization and control of biped robots in double-support phase under perturbing external forces

To realize the dynamic balance optimization and control of biped robots under the perturbing external forces in the double-support phase, a systematic scheme is proposed in this paper. First, a constrained dynamic model of biped robots and a reduced order dynamical model for the double-support phase are formulated. Considering the dynamic external wrench applied on biped robots, we present a dynamic force distribution approach based on quadratic objective function for computing the optimal contact forces to equilibrate the dynamic external wrench. As a result, the sum of the normal force components is minimized for enhancing safety and energy saving. Then, one primary recurrent neural network (RNN) is adopted to solve the optimization problem subject to both equality and inequality constraints. For the derived optimized contact force and motion, hybrid motion/force control is proposed based on another RNN to approximate unknown dynamic functions. Adaptive learning algorithms for learning the parameters of the RNN are provided as well. The proposed control can deal with the uncertainties including approximation errors and external disturbances. Extensive simulations are presented to demonstrate the effectiveness of the proposed optimization and control approach.

Landing Control on a Mobile Platform for Multi-copters using an Omnidirectional Image Sensor

This paper proposes a vision-based target following and landing system for a quadrotor vehicle on a moving platform. The system employs a vision-based landing site detection and locating algorithm using an omnidirectional lens. The latest smartphone was attached to the UAV and served as an on-board image acquisition and process unit. Measurements from the omnidirectional camera are combined with a proper dynamic model in order to estimate position and velocity of the moving platform. An adaptive control scheme was implemented on the flight computer to deal with unknown disturbances in outdoor environments. The system was validated on a quadrotor UAV and the vehicle successfully landed on the moving platform during outdoor flight tests.

Robust load‐frequency control in interconnected power systems

This study describes a robust load-frequency control (LFC) scheme in a two-area interconnected power system with uncertain disturbances. A sector-bounded H∞ control approach is used for compensating of the non-linearities based on a minimum order dynamic LFC model to avoid the complexity of a high-order model. The simulation in time domain from the use of the proposed controller has been compared with the use of a conventional proportional–integral (PI) type controller affected by the same load change. The simulated results have proved the significant improvement over the PI controller and have verified the effectiveness of the proposed robust H∞ controller which can minimise the frequency deviations significantly. This approach treats the tie-line power exchanges in the presences of external disturbance, parameter uncertainties and accidental crashing of generating units as the structural or model uncertainties discussed in this study. Simulation results also show that the proposed H∞ controller guarantees robust performance and fast response under a wide range of operating conditions and system uncertainties.

Anisotropic AC Magnetic Susceptibility in (Ga,Mn)As Films

Ferromagnetic semiconductor (Ga, Mn)As has emerged as the most thoroughly studied material for semiconductor spintronic applications, showing excellent magnetic properties that are usually described by the single-domain model [1]. However, certain uncertainties about magnetic phase structure and their dynamic properties of this system still remain unresolved. In this study, we systematically carry out both dc and ac magnetic measurements as a function of temperature and applied magnetic field in (Ga, Mn)As films with nominal Mn concentration of 5.0% grown by molecular beam epitaxy. The ac susceptibility vs. temperature shows similar results to those reported previously [2,3]: two peaks are observed with magnetic field H along [100], one close to T C and one close to T C /2, while one peak close to T C is observed with H along [1-10], and one peak close to T C /2 is seen for H along [110]. These results are consistent with dc magnetization measurements along these three axes. Careful analysis of hysteresis loops and of frequency-dependent ac susceptibility leads to the unambiguous conclusion that the ac susceptibility peak near T C occurs because of transition from paramagnetic to ferromagnetic phase; and the peak near T C /2 occurs because of the onset of a biaxial domain structure [4]. Specifically, ac susceptibility near T C involves a 180 degree magnetization flip along the [1-10] axis (i.e., the uniaxial easy axis), while the peak of the ac susceptibility near T C /2 originates from a magnetization flip between two biaxial easy axes with an angular separation of θ(T), arising from the competition between uniaxial and cubic anisotropy. Due to the difference between these two mechanisms, frequency dependences of ac susceptibilities in these two temperature regions are also quite different, providing additional information on both biaxial and uniaxial domain structures in (Ga, Mn)As films. In this connection, magnetic dynamic properties (such as the relaxation times) are analyzed and discussed using various dynamic models in order to allow us to get better insight into the evolution of magnetic domain transitions in (Ga, Mn)As films. The present observations on magnetic domain transitions and their dynamics provide new information relevant to spintronic applications such as memory and logic devices. This work was supported by the NSF Grant DMR14-00432.

Dynamic response and governor tuning of a long penstock pumped-storage hydropower plant equipped with a pump-turbine and a doubly fed induction generator

In this paper, the dynamic response of a long penstock pumped-storage hydropower plant which is equipped with a single pump-turbine and a doubly-fed induction machine, is analyzed in detail in generating mode. The pumped-storage hydropower plant is connected to a small island power system with thermal generation, and provides load–frequency control under the orders of an automatic generation control system. The output power of the pumped-storage hydropower plant is assumed to be controlled by the rotor-side frequency converter. The unit running speed is controlled by an isochronous PI governor. The dynamic response of the pumped-storage hydropower plant is analyzed by using a linearized reduced order dynamic model, which considers the elastic water column effects in the penstock. Two governor tuning criteria are proposed in the paper: one is devised from the root locus analysis of the plant dynamic model, and the other one is based on a Pareto approach. The proposed tuning criteria are compared with each other and with a recently published tuning criterion through a set of commonly used performance indexes and by means of simulations with a nonlinear dynamic model.