Loss comparison between an SPWM and harmonic elimination excited small, (<1kW) induction motor drive using Pspice simulation and calorimetry

Adopting square wave excitation to drive induction motors (IMs) can substantially reduce inverter switching losses. However, the low-order time harmonics inherent in the output voltage generates parasitic torques that degrade motor performance and reduce efficiency. In this paper, a novel harmonic elimination modulation technique with full voltage control is studied as an interesting and alternative means of operating small (<1kW) IM drives efficiently. A fully verified harmonic elimination scheme, which removes the 5th, 7th, 11th, 13th and 17 th time harmonics, was implemented and applied to an IGBT driven IM. The power losses incurred in the inverter and the IM as a result of the switching scheme have been determined. © 2008 Crown copyright.

Pulsed field magnetization of a high temperature superconducting motor

As we known, the high temperature (77 K) superconducting (HTS) motor is considered as a competitive electrical machine by more and more people. There have been various of designs for HTS motor in the world. However, most of them focus on HTS tapes rather than bulks. Therefore, in order to investigate possibility of HTS bulks on motor application, a HTS magnet synchronous motor which has 75 pieces of YBCO bulks surface mounted on the rotor has been designed and developed in Cambridge University. After pulsed field magnetization (PFM) process, the rotor can trap a 4 poles magnetic field of 375 mT. The magnetized rotor can provide a maximum torque of 49.5 Nm and a maximum power of 7.8 kW at 1500 rpm. © 2010 IEEE.

Short- and long-term changes in joint co-contraction associated with motor learning as revealed from surface EMG.

In the field of motor control, two hypotheses have been controversial: whether the brain acquires internal models that generate accurate motor commands, or whether the brain avoids this by using the viscoelasticity of musculoskeletal system. Recent observations on relatively low stiffness during trained movements support the existence of internal models. However, no study has revealed the decrease in viscoelasticity associated with learning that would imply improvement of internal models as well as synergy between the two hypothetical mechanisms. Previously observed decreases in electromyogram (EMG) might have other explanations, such as trajectory modifications that reduce joint torques. To circumvent such complications, we required strict trajectory control and examined only successful trials having identical trajectory and torque profiles. Subjects were asked to perform a hand movement in unison with a target moving along a specified and unusual trajectory, with shoulder and elbow in the horizontal plane at the shoulder level. To evaluate joint viscoelasticity during the learning of this movement, we proposed an index of muscle co-contraction around the joint (IMCJ). The IMCJ was defined as the summation of the absolute values of antagonistic muscle torques around the joint and computed from the linear relation between surface EMG and joint torque. The IMCJ during isometric contraction, as well as during movements, was confirmed to correlate well with joint stiffness estimated using the conventional method, i.e., applying mechanical perturbations. Accordingly, the IMCJ during the learning of the movement was computed for each joint of each trial using estimated EMG-torque relationship. At the same time, the performance error for each trial was specified as the root mean square of the distance between the target and hand at each time step over the entire trajectory. The time-series data of IMCJ and performance error were decomposed into long-term components that showed decreases in IMCJ in accordance with learning with little change in the trajectory and short-term interactions between the IMCJ and performance error. A cross-correlation analysis and impulse responses both suggested that higher IMCJs follow poor performances, and lower IMCJs follow good performances within a few successive trials. Our results support the hypothesis that viscoelasticity contributes more when internal models are inaccurate, while internal models contribute more after the completion of learning. It is demonstrated that the CNS regulates viscoelasticity on a short- and long-term basis depending on performance error and finally acquires smooth and accurate movements while maintaining stability during the entire learning process.

Task-dependent coordination of rapid bimanual motor responses.

Optimal feedback control postulates that feedback responses depend on the task relevance of any perturbations. We test this prediction in a bimanual task, conceptually similar to balancing a laden tray, in which each hand could be perturbed up or down. Single-limb mechanical perturbations produced long-latency reflex responses ("rapid motor responses") in the contralateral limb of appropriate direction and magnitude to maintain the tray horizontal. During bimanual perturbations, rapid motor responses modulated appropriately depending on the extent to which perturbations affected tray orientation. Specifically, despite receiving the same mechanical perturbation causing muscle stretch, the strongest responses were produced when the contralateral arm was perturbed in the opposite direction (large tray tilt) rather than in the same direction or not perturbed at all. Rapid responses from shortening extensors depended on a nonlinear summation of the sensory information from the arms, with the response to a bimanual same-direction perturbation (orientation maintained) being less than the sum of the component unimanual perturbations (task relevant). We conclude that task-dependent tuning of reflexes can be modulated online within a single trial based on a complex interaction across the arms.

Design method of an innovative motor for an intra-aortic ventricular assist device

A permanent-magnet motor has been designed for an innovative axial-flow ventricular assist device (VAD), to be placed in the descending aorta, intended to offload the left ventricle and augment renal perfusion in patients with congestive heart failure (CHF). For this application, an intra-aortic impeller with a built-in permanent magnet rotor is driven by an extraaortic stator working in synchronism with the natural heart. To meet this need, a two-dimensional analytical model has been developed in the MATLAB environment to estimate machine parameters; finite element analysis (FEA) has been used to refine the results. A prototype blood pump equipped with an innovative motor designed from the procedure above has been tested in a mock loop representing the human circulatory system. The performance of VAD incorporating the motor is presented. © 2009 IEEE.

Deliberation in the motor system: reflex gains track evolving evidence leading to a decision.

Both decision making and sensorimotor control require real-time processing of noisy information streams. Historically these processes were thought to operate sequentially: cognitive processing leads to a decision, and the outcome is passed to the motor system to be converted into action. Recently, it has been suggested that the decision process may provide a continuous flow of information to the motor system, allowing it to prepare in a graded fashion for the probable outcome. Such continuous flow is supported by electrophysiology in nonhuman primates. Here we provide direct evidence for the continuous flow of an evolving decision variable to the motor system in humans. Subjects viewed a dynamic random dot display and were asked to indicate their decision about direction by moving a handle to one of two targets. We probed the state of the motor system by perturbing the arm at random times during decision formation. Reflex gains were modulated by the strength and duration of motion, reflecting the accumulated evidence in support of the evolving decision. The magnitude and variance of these gains tracked a decision variable that explained the subject's decision accuracy. The findings support a continuous process linking the evolving computations associated with decision making and sensorimotor control.

DOPAMINE D2 RECEPTOR MECHANISMS CONTRIBUTE TO AGE-RELATED COGNITIVE DECLINE - THE EFFECTS OF QUINPIROLE ON MEMORY AND MOTOR-PERFORMANCE IN MONKEYS

The D2 dopamine (DA) receptor agonist, quinpirole, was characterized in young adult monkeys, young reserpine-treated monkeys and aged monkeys to assess the contribution of DA to age-related loss of prefrontal cortical (PFC) cognitive function, Monkeys were tested on a delayed response memory task that depends on the PFC, and a fine motor task that taps the functions of the motor cortex, In young adult monkeys, low quinpirole doses impaired performance of the PFC and fine motor tasks, while higher doses improved memory performance and induced dyskinesias and ''hallucinatory-like'' behaviors. The pattern of the quinpirole response in reserpine-treated monkeys suggested that the impairments in delayed response and fine motor performance resulted from drug actions at D2 autoreceptors, while the improvement in delayed response performance, dyskinesias and ''hallucinatory-like'' behaviors resulted from actions at postsynaptic receptors. In aged monkeys, low doses of quinpirole continued to impair fine motor performance, but lost their ability to impair delayed response performance. The magnitude of cognitive improvement and the incidence of ''hallucinatory-like'' behaviors were also reduced in the aged animals, suggesting some loss of postsynaptic D2 receptor function, The pattern of results is consistent with the greater loss of DA from the PFC than from motor areas in aged monkey brain (Goldman-Rakic and Brown, 1981; Wenk et al., 1989), and indicates that DA depletion contributes significantly to age-related cognitive decline.

Motor control is decision-making.

Motor behavior may be viewed as a problem of maximizing the utility of movement outcome in the face of sensory, motor and task uncertainty. Viewed in this way, and allowing for the availability of prior knowledge in the form of a probability distribution over possible states of the world, the choice of a movement plan and strategy for motor control becomes an application of statistical decision theory. This point of view has proven successful in recent years in accounting for movement under risk, inferring the loss function used in motor tasks, and explaining motor behavior in a wide variety of circumstances.