Space vector modulation based fast speed response field-orientation control of induction motor drive with adaptive neural integrator

This paper presents a novel fast speed response control strategy for the poly-phase induction motor drive system based on flux angle. The control scheme is derived in rotor field coordinates and employs the estimation of the rotor flux and its position. An adaptive notch filter is proposed to eliminate the dc component of the integration of signals used for the rotor flux estimation. To improve the performance of the rotor flux estimator, derivative term of the back emf is incorporated in the system. The voltage components in the synchronous reference frame are generated in the controllers which are transformed to stationary reference frame for driving the motor. Space vector modulation technique is used here. Simulation of the drive system was carried out and the results were compared with those obtained for a system that produces the above mentioned voltage components using the conventional PI controller. It is observed that the proposed control methodology provides faster response than the conventional PI controller incorporated system.

A high performance position sensorless surface permanent magnet synchronous motor drive based on flux angle

A position sensorless Surface Permanent Magnet Synchronous Motor (SPMSM) drive based on flux angle is presented in this paper. The motor equations are written in rotor fixed d-q reference frame. A PID controller is used to process the speed error to generate the reference torque current keeping the magnetizing current fixed. The estimated stator flux using Recurrent Neural Network (RNN) is used to find out the rotor position. The flux angle and the reference current phasor angle are used in vector rotator to generate the reference phase currents. Hysteresis current controller block controls the switching of the 3-phase inverter to apply voltage to the motor stator. Simulation studies on different operating conditions indicate the acceptability of the drive system. The drive system only requires a speed transducer and is free from position sensor requirement. The proposed control scheme is robust under load torque disturbances and motor parameter variations. It is also simple and low cost to implement in a practical environment.

Genetic algorithm based PI controller tuning for induction motor drive with ANN flux estimator

This paper presents a Genetic Algorithm (GA) based fast speed response controller for poly-phase induction motor drive. Here the proportional and integral gains of PI controller are optimized by GA to achieve quick speed response. An adaptive Recurrent Neural Network (RNN) with Real Time Recurrent Learning (RTRL) algorithm is proposed to estimate rotor flux. An online tuning scheme to update the weight of RNN is presented to overcome stator resistance variation problem. This tuning scheme requires torque estimator to calculate the torque error. Space vector modulation (SVM) technique is used to produce the motor input voltage. Simulation tests have been performed to study the dynamic performances of the drive system for both the classical PI and the genetic algorithm based PI controllers.

Three algorithms for learning artificial neural network: A comparison for induction motor flux estimation

This paper presents a comparative study of three algorithms for learning artificial neural network. As neural estimator, back-propagation (BP) algorithm, uncorrelated real time recurrent learning (URTRL) algorithm and correlated real time recurrent learning (CRTRL) algorithm are used in the present work to learn the artificial neural network (ANN). The approach proposed here is based on the flux estimation of high performance induction motor drives. Simulation of the drive system was carried out to study the performance of the motor drive. It is observed that the proposed CRTRL algorithm based methodology provides better performance than the BP and URTRL algorithm based technique. The proposed method can be used for accurate measurement of the rotor flux.

Function and structure of the mirror neuron system in autism

 Utilizing MRI, this thesis identified wide-spread brain abnormalities in autism. White matter deficits were more pronounced in the left hemisphere, attributable to atypical myelination. Regarding the mirror neuron system, functional anomalies were situated in the right, dorsal, premotor cortex which further demonstrated reduced functional connectivity with the inferior parietal lobule.

Fish oil diet associated with acute reperfusion related hemorrhage, and with reduced stroke-related sickness behaviors and motor impairment

Ischemic stroke is associated with motor impairment and increased incidence of affective disorders such as anxiety/clinical depression. In non-stroke populations, successful management of such disorders and symptoms has been reported following diet supplementation with long chain omega-3-polyunsaturated-fatty-acids (PUFAs). However, the potential protective effects of PUFA supplementation on affective behaviors after experimentally induced stroke and sham surgery have not been examined previously. This study investigated the behavioral effects of PUFA supplementation over a 6-week period following either middle cerebral artery occlusion or sham surgery in the hooded-Wistar rat. The PUFA diet supplied during the acclimation period prior to surgery was found to be associated with an increased risk of acute hemorrhage following the reperfusion component of the surgery. In surviving animals, PUFA supplementation did not influence infarct size as determined 6 weeks after surgery, but did decrease omega-6-fatty-acid levels, moderate sickness behaviors, acute motor impairment, and longer-term locomotor hyperactivity and depression/anxiety-like behavior.

Interrater reliability assessment using the Test of Gross Motor Development-2

Objectives: The aim was to examine interrater reliability of the object control subtest from the Test of Gross Motor Development-2 by live observation in a school field setting. Design:: Reliability Study - cross sectional. Methods: Raters were rated on their ability to agree on (1) the raw total for the six object control skills; (2) each skill performance and (3) the skill components. Agreement for the object control subtest and the individual skills was assessed by an intraclass correlation (ICC) and a kappa statistic assessed for skill component agreement. Results: A total of 37 children (65% girls) aged 4-8 years (M= 6.2, SD=0.8) were assessed in six skills by two raters; equating to 222 skill tests. Interrater reliability was excellent for the object control subset (ICC= 0.93), and for individual skills, highest for the dribble (ICC= 0.94) followed by strike (ICC= 0.85), overhand throw (ICC= 0.84), underhand roll (ICC= 0.82), kick (ICC= 0.80) and the catch (ICC= 0.71). The strike and the throw had more components with less agreement. Conclusions: Even though the overall subtest score and individual skill agreement was good, some skill components had lower agreement, suggesting these may be more problematic to assess. This may mean some skill components need to be specified differently in order to improve component reliability.

The association between attributions of responsibility for motor vehicle accidents and patient satisfaction: a study within a no-fault injury compensation system

This study set out to test the relationship between attributions of responsibility for motor vehicle accidents and satisfaction with personal injury compensation systems.