Speed Disturbance Research Articles

Comparative study of impact of hemodialysis and renal transplantation on cognitive functions in ESRD patients

Cognitive impairment is defined as a newly appeared deficit in at least two areas of cognitive functions, including disturbances in memory, executive functioning, attention or speed of information processing, perceptual motor abilities, or language. Cognitive impairment is highly prevalent in ESRD patients when compared with the general population. It has also been associated with a decreased quality of life. Cognitive functions in patients with ESRD showed improvement with dialysis and renal transplantation. These findings illustrate the potential importance of evaluating and comparing the effects of hemodialysis and transplantation regarding cognitive performance and thus quality of life in ESRD patients and normal subjects. This study was carried out in 100 patients (50 ESRD patients on regular hemodialysis for at least 6 months and 50 post-transplant patients who had maintained successful kidney graft for at least 3 months). All patients underwent laboratory and psychometric scoring tests, including trail making test part A, trail making test part B, digit span, and mini-mental state examination. Thirty healthy adults matched by age and sex served as a control group. The results showed significant differences in cognitive function tests results between transplant and hemodialysis patients (P<0.01), suggesting that transplant patients were superior in their cognitive performance, with the correction of anemia being the most important factor for improving cognitive performance in both groups. There were no significant differences between transplant patients and control subjects in psychometric measures (P>0.05). ConclusionRenal transplantation as a modality of treatment, in ESRD patients, is superior to hemodialysis in terms of cognitive performance improvement.

Virtual Inertia Control of D-PMSG Based on the Principle of Active Disturbance Rejection Control

The virtual inertia control (VIC) of wind turbine with directly-driven permanent-magnet synchronous generator (D-PMSG) can act similarly to the conventional synchronous generator in inertia response and frequency control, thereby supporting the system frequency stability. However, because the wind speed is inconstant and changeable to a certain extent and the D-PMSG is a complex nonlinear system, there are great difficulties in the virtual inertia optimal control of the D-PMSG. Based on the design principle of the active disturbance rejection control (ADRC), this paper presents a new VIC strategy for the D-PMSG from the perspective of power disturbance suppression in the system. The strategy helps fulfill the power grid disturbance estimation and compensation by means of the extended state observer (ESO) so as to improve the disturbance-resisting performance of the system. Compared with conventional proportional-derivative virtual inertia control (PDVIC), this method, which is of better adaptability and robustness, can not only improve the property of the DPMSG responding to the system frequency but also reduce the influence of wind speed disturbance. The simulation and experiment results have verified the effectiveness and feasibility of the VIC based on the ADRC.

The physics of empirical nuclei for spontaneous traffic breakdown in free flow at highway bottlenecks

Based on an empirical study of real field traffic data measured in 1996–2014 through road detectors installed on German freeways, we reveal physical features of empirical nuclei for spontaneous traffic breakdown in free flow at highway bottlenecks. A microscopic stochastic three-phase traffic model of the nucleation of spontaneous traffic breakdown presented in the article explains the empirical findings. It turns out that in the most cases a nucleus for the breakdown occurs through an interaction of one of waves in free flow with an empirical permanent speed disturbance localized at a highway bottleneck. The wave is a localized structure in free flow, in which the total flow rate is larger and the speed averaged across the highway is smaller than outside the wave. The waves in free flow appear due to oscillations in the percentage of slow vehicles; these waves propagate with the average speed of slow vehicles in free flow. Any of the empirical waves exhibits a two-dimensional asymmetric spatiotemporal structure: Wave’s characteristics are different in different highway lanes.

Iterative Local ANFIS-Based Human Welder Intelligence Modeling and Control in Pipe GTAW Process: A Data-Driven Approach

Combining human welder (with intelligence and versatility) and automated welding systems (with precision and consistency) can lead to intelligent welding systems. This paper aims to present a data-driven approach to model human welder intelligence and use the resultant model to control automated gas tungsten arc welding process. To this end, an innovative machine-human cooperative virtualized welding platform is teleoperated to conduct training experiments. The welding current is randomly changed to generate fluctuating weld pool surface and the human welder tries to adjust his arm movement (welding speed) based on his observation on the real-time weld pool feedback/image superimposed with an auxiliary visual signal which instructs the welder to increase/reduce the speed. Linear model is first identified from the experimental data to correlate welder's adjustment on the welding speed to the 3-D weld pool surface and a global adaptive neuro-fuzzy inference system (ANFIS) model is then proposed to improve the model accuracy. To better distill the detailed behavior of the human welder, K -means clustering is performed on the input space such that a local ANFIS model is identified. To further improve the accuracy, an iterative procedure has been performed. Compared to the linear, global and local ANFIS model, the iterative local ANFIS model provides better modeling performance and reveals more detailed intelligence human welders possess. To demonstrate the effectiveness of the proposed model as an effective intelligent controller, automated control experiments have been conducted. Experimental results verified that the controller is robust under different welding currents and welding speed disturbance.

An integrated control system for sparse matrix converter interfacing PMSG with the grid

Abstract This paper presents an integrated control system for Sparse Matrix Converter (SMC) to interface Permanent Magnet Synchronous Generator (PMSG) based wind turbine unit with the power grid. A carrier based PWM technique is extended and adapted for the SMC. Details of the proposed switching strategy and derivations of the modulation functions for both the rectifier and inverter stages of the SMC are presented. The inverter stage is controlled to regulate the speed of the PMSG for maximum power extraction. In addition, the rectifier stage of the SMC is controlled to deliver the generated active power from the PMSG to the grid at the required power factor to satisfy the reactive power demand. Moreover, the proposed interface system is adaptively synchronized with the grid. The Multi-Output Recursive Least Square (MO-RLS) algorithm is proposed to estimate the phase angle of the grid voltage. Furthermore, active damping scheme is integrated with the proposed control system to attenuate the oscillations caused by the LC filter of the rectifier stage. Numerical simulations are conducted to investigate the effectiveness and the fast dynamic performance of the proposed control system based on MO-RLS even during the speed disturbance. The proposed interface system succeeds to control active power with the desired power factor demand and to damp the oscillations of the SMC current and voltage.

Maximum Power Point Tracking Strategy for Large-Scale Wind Generation Systems Considering Wind Turbine Dynamics

Under the global trend of renewable energy development, various advanced techniques such as forecasting algorithm, intelligent computation, and optimal control are expected to make the complex and uncertain renewable energy system stable and profitable in the near future. This paper presents a new control strategy for large-scale wind energy conversion systems to achieve a balance between power output maximization and operating cost minimization. First, an intelligent maximum power point tracking (IMPPT) algorithm is proposed such that short-term wind speed prediction, wind turbine dynamics, and MPPT are collectively considered to improve system efficiency. Second, in view of a spatial and temporal distribution of wind speed disturbances, a box uncertainty set is embedded in the forecast wind speed, which is likely more realistic for practicing engineers. Then, the IMPPT and box uncertainties are applied to the wind energy conversion system (WECS) control strategy, which is formulated as a min-max optimization problem and efficiently solved with semi-definite programming (SDP). Finally, a comparison with the conventional MPPT control method demonstrates that the proposed approach can obtain higher efficiency, which validates this paper.

Second-Order Cone Programming-Based Optimal Control Strategy for Wind Energy Conversion Systems Over Complete Operating Regions

An efficient control strategy of a wind energy conversion system (WECS) plays a crucial role in wind power utilization. In this paper, a novel multivariable control strategy for a variable-speed variable-pitch WECS is proposed. It is designed for the complete operating regions of a wind turbine, including both of the partial load region and the full load region, with the objectives of maximizing energy capture, smoothing power output, alleviating drive train transient loads, and reducing pitch actuator activities. In particular, this paper considers the wind speed disturbance as norm-bounded, instead of deterministic or chance constraints in the widely used quadratic control methods such as linear quadratic Gaussian control and model predictive control. Moreover, the WECS control with the norm-bounded disturbance is formulated as a second-order cone programming (SOCP) problem that has not been previously employed for wind power control. Finally, simulation results are provided to demonstrate the validity of the proposed method.

Evaluation of a wind speed estimator for effective hub-height and shear components

Estimates of the effective wind speed disturbances acting on a wind turbine are useful in a variety of control applications. With some simplifications, it is shown that for zero yaw error, any wind field interacting with a turbine can be equivalently described using a hub-height (uniform) component as well as linear horizontal and vertical shear components. A Kalman filter-based wind speed estimator is presented for estimation of these effective hub-height and shear components. The wind speed estimator is evaluated in the frequency domain using the FAST aeroelastic simulator with the National Renewable Energy Laboratory's 5 MW reference wind turbine model and realistic hub-height and shear disturbances. In addition, the impact of the inflow model, used to simulate the rotor aerodynamics, on the Kalman filter performance is investigated. It is found that the estimator accuracy strongly depends on the inflow model used. In general, the estimator performs well up to a bandwidth of 1 Hz when the inflow model used for simulation matches the model used to create the linear Kalman filter model and blade pitch angle remains close to the linearization operating point. However, inaccuracies in the linear model of the turbine when dynamic inflow is used for simulation as well as nonlinearities in the turbine dynamics due to blade pitch actuation cause performance to degrade. Finally, the improvement gained by employing a non-causal wind speed estimator is assessed, showing a minor increase in performance. Copyright © 2014 John Wiley & Sons, Ltd.

Robust Adaptive Fault Tolerant Pitch Control of Wind Turbines

Inaccuracy in linear modeling of wind turbines, effects of wind speed disturbance, and faults in components of the closed-loop system increase the need for advanced controllers in wind energy conversion systems. In this article, an adaptive pitch controller is developed to regulate the generator speed in region 3. Also, an adaptive feed-forward term is augmented to improve the generator speed regulation in presence of the wind speed disturbance. Parameters of the controller are adaptively adjusted based on the improved dead-zone modification rule that guarantees closed-loop stability and zero regulation error in presence of the unstructured modeling uncertainties, step-like wind speed disturbance, and faults in pitch actuator. Proposed controller is compared to the baseline proportional-integral controller for controls advanced research turbine. Simulation results confirm the improvement in closed-loop regulation performance with proposed robust adaptive controller.

The Impact of Power System Voltage Regulation Caused by Wind Disturbance

It studies the impacts of the wind speed disturbance such as the gradient wind and gust on the active power, reactive power and voltage of the system. In the process of wind speed disturbance, double fed wind turbine increases or reduces the reactive output of wind turbine timely according to the changes of system voltage, ensure the machine terminal voltage to operate in the normal range .

Influence of Control Structures and Load Parameters on Performance of a Pseudo Direct Drive

The paper describes an in-depth and systematic analysis of a pseudo direct drive permanent magnet machine in closed loop control. Due to the torque being transmitted from the high-speed rotor (HSR) to the low-speed rotor (LSR), through a relatively low stiffness magnetic gear with non-linear characteristics, speed oscillations appear in the drive output with a conventional proportional integral (PI) controller. Therefore two candidate controllers have been proposed as an alternative to the PI control and all controllers have been optimally tuned with a genetic algorithm against a defined criterion. Furthermore, closed loop models are established in the complex frequency domain to determine the system damping and the cause of the oscillations. Consequently, the best controller structure that improves the dynamic behaviour of the system in terms of speed tracking and disturbance rejection could be identified, based on the frequency domain analysis. Experimental results are presented to validate the analysis and the proposed control technique.

Hybrid Anti-Windup Fuzzy PI Controller Based Direct Torque Control of Three Phase Induction Motor

This paper presents improved Fuzzy Logic Controller (FLC) of the Direct Torque Control (DTC) of Three-Phase Induction Motor (IM) for high performance and torque control industrial drive applications. The performance of the IM using PI Controllers and general fuzzy controllers are meager level under load disturbances and transient conditions. The FLC is extended to have a less computational burden which makes it suitable for real time implementation particularly at constant speed and torque disturbance operating conditions. Hybrid control has advantage of integrating a superiority of two or more control techniques for better control performances. A fuzzy controller offers better speed responses for startup and large speed errors. If the nature of the load torque is varied, the steady state speed error of DTC based IM drive with fuzzy logic controller becomes significant. To improve the performance of the system, a new control method, Hybrid fuzzy PI control is proposed. The effectiveness of proposed method is verified by simulation based on MATLAB. The proposed Hybrid fuzzy controller has adaptive control over load toque variation and can maintain constant speed.

Predictive control of an experimental wind turbine using preview wind speed measurements

AbstractThe development of a more reliable method of measuring the wind field upstream of a turbine (light detection and ranging) has enabled the implementation of feedforward‐related control strategies to enhance the control performance of wind turbines. By incorporating wind speed measurements, the controller is able to anticipate upon future events and thereby improve structural load mitigation and power regulation of the wind turbine. This work aims to experimentally verify the benefits of using predictive and feedforward‐based control strategies over industry standard control solutions. To achieve this, both a feedforward and a model predictive control strategy are presented, which have been validated on an experimental wind turbine in a wind tunnel. Both the model predictive controller and feedforward algorithm have shown superior performance over a baseline controller in terms of rotor speed regulation under wind speed disturbances. The experiment confirmed that a phase advantage in the control input of the predictive controller led to this performance increase. It has also been found that knowledge of just the current wind speed can already significantly increase the control performance. Copyright © 2014 John Wiley &amp; Sons, Ltd.

The relationship of cognitive impairment with neurological and psychiatric variables in multiple sclerosis patients

Objective. Cognitive impairment (CI) in multiple sclerosis (MS) can develop any time. CI is associated with the degree of neuronal loss, but disease duration, fatigue, comorbid affective disorder, and drug dose may also affect cognition. Our aim was to assess which cognitive domain was disturbed primarily in mild MS patients and to see whether CI was related with clinical and psychiatric features. Method. Neurological and psychiatric evaluation of 31 MS patients and 31 age, sex, and education-matched healthy controls were made with Structured Clinical Interview for Axis I Disorders (SCID-I). Depression, anxiety, functionality, fatigue, and disability scoring were determined with Hamilton Depression-Anxiety scales, Global Assessment of Functionality, Fatigue Severity and Expanded Disability Status Scales. Cognitive functions were assessed using Mini Mental, Serial Digit Learning, Verbal and Nonverbal Cancellation, Stroop and Rey Auditory Verbal Learning tests. Results. Retrieval from long-term memory and psychomotor speed were significantly worse in MS group. CI was correlated with disease duration, number of attacks, and physical disability but not with depression and anxiety severity. Disease duration predicted disturbances in recall and psychomotor speed, whereas fatigue and disability predicted depression. Conclusion. Psychomotor speed and memory were primarily impaired in MS patients, and CI was closely associated with clinical aspects of MS rather than with depression and anxiety.

A Neural Network Controller for Variable-Speed Variable-Pitch Wind Energy Conversion Systems Using Generalized Minimum Entropy Criterion

This paper considers the neural network controller design problem for variable pitch wind energy conversion systems (WECS) with non-Gaussian wind speed disturbances in the stochastic distribution control framework. The approach here is used to directly model the unknown control law based on a fixed neural network (the number of layers and nodes in a neural network is fixed) without the need to construct a separate model for the WECS. In order to characterize the randomness of the WECS, a generalized minimum entropy criterion is established to train connection weights of the neural network. For the train purpose, both kernel density estimation method and sliding window technique are adopted to estimate the PDF of tracking error and entropies. Due to the unknown process dynamics, the gradient of the objective function in a gradient-descent-type algorithm is estimated using an incremental perturbation method. The proposed approach is illustrated on a simulated WECS with non-Gaussian wind speed.

Impact of Wind Farms on the Voltage of the Grid Integrated under the Ramp Changing Wind Speed

The wind speed simulation model was given in this paper, combined with the power system analysis software (PSD-BPA) transient calculation of wind generator models, it implemented the wind speed disturbance of wind farms and the entire network voltage analysis. Combining the practical power grid in china, research on the power grid voltage fluctuation of the level after the large-scale wind farms integrated the system, and relevant the conclusions: In the process of wind disturbance, there is no angle stability of synchronous generator in the system, doubly-fed induction generator could emit and absorb reactive power, and thus could be able to maintain voltage stability.

A tutorial on learning human welder's behavior: Sensing, modeling, and control

Human welder's experiences and skills are critical for producing quality welds in manual GTAW process. Learning human welder's behavior can help develop next generation intelligent welding machines and train welders faster. In this tutorial paper, various aspects of mechanizing the welder's intelligence are surveyed, including sensing of the weld pool, modeling of the welder's adjustments and this model-based control approach. Specifically, different sensing methods of the weld pool are reviewed and a novel 3D vision-based sensing system developed at University of Kentucky is introduced. Characterization of the weld pool is performed and human intelligent model is constructed, including an extensive survey on modeling human dynamics and neuro-fuzzy techniques. Closed-loop control experiment results are presented to illustrate the robustness of the model-based intelligent controller despite welding speed disturbance. A foundation is thus established to explore the mechanism and transformation of human welder's intelligence into robotic welding system. Finally future research directions in this field are presented.

Fluência e Prosódia: Aspectos Diferenciais Frente aos Distúrbios

Objective. To establish the difference between the disorders of flu ency and prosody. Method. It is a review of literature on the fluency and Prosody front to their disorders. Results. Fluency is characterized by the ability to produce a spontaneous fluid speech and its disor ders are termed as fluency disorders, in which occur disturbances in rhythm, intonation and speed, when there is stress to speak. These disorders can be classified as normal, abnormal or ambiguous. The Prosody is defined as the element that verbal oral production struc ture is capable of segmenting speech sounds that when formulating the syllables, raises a rhythmic structure. Their disorders are classified into aprosodia and hiperprosodia. Conclusion. The characterization of prosody and of fluency mixes in many papers. Although different the fluency disorders and disturbances of prosody carry differences as to its interpretation in the light of the theoretical bases that mark their concepts.

PSO Based Self-Tuning PID Pitch Control for Wind Power Generation System

Most variable speed wind turbines have pitch angle control mechanisms and one of their objectives is to protect turbines when the wind speed is too high. Pitch angle control is the most common means for adjusting the aerodynamic torque of the wind turbine when wind speed is above rated speed. The paper deals with optimal tuning of a PID controller for pitch angle control in wind turbines using particle swarm optimization (PSO) algorithm. The particle swarm optimization is used for achieving the correction coefficient values of deviation which are sent to the controller so that the control effect of chlorination system is improved. Simulation results prove the effectiveness of proposed control strategy. System can eliminate the wind speed disturbance and provide good transient and robust performance.

Air-Fuel Ratio Fuzzy PID Control for Coal-Bed Gas Engine Based on Fuzzy PID Feedforward

In order to eliminate the adverse effects of coal-bed gas concentration disturbance to coal-bed gas engine air-fuel ratio control and the large pure time-delay existed in signal response of methane transducer, a fuzzy PID feedforward flow control plan was proposed for gas supply system. Fast and efficient flow control was performed in advance according to air-fuel ratio control requirements to eliminate air-fuel ratio control delays caused by the coal bed methane concentration disturbance. Based on the mentioned feedforward flow control plan, considering the premix coal-bed gas engine air-fuel ratio fluctuations arising from engine speed disturbances, a fuzzy PID closed-loop control scheme was proposed. By analyzing different air-fuel ratio control characteristics in transient condition and steady condition, the different closed-loop control of the air-fuel ratio was used to suppress air-fuel ratio fluctuations caused by engine condition changes. Compared to traditional PID control, the simulation results show that the air-fuel ratio fuzzy PID closed control scheme based on fuzzy PID feedforward flow control has ideal control effect, preferable stability and robustness. The air-fuel ratio control delays caused by the coal-bed methane concentration disturbance is well solved, and the problem of air-fuel ratio disturbance is well solved when the engines working condition changes, meeting the pre-mixed coal-bed gas engine air-fuel ratio control requirements.