PWM motor control: Model and servo analysis

In recent years, the performance requirements of high power servo motor systems utilizing pulse width modulated (PWM) switching amplifiers have steadily increased. These PWM motor amplifiers perform an important function in the d.c. servo system by boosting the low level command signal to the high voltage and current levels required by the motor. Ideally, this power gain is to be constant over all input frequencies but, in reality, gain is frequency dependent which affects system dynamics. The amplifier gain and phase versus frequency relationships an*i amplifier noise and d.c. offsets which may affect system response must be known to the servo designer to properly design the motor control system. The switching effects of the PWM amplifier may result in making the overall system unstable if the system bandwidth is kept high with respect to the PWM switching frequency. Since the standard servo design techniques utilize linear system modeling, analysis, and compensation, it would be very advantageous to the design engineer to have a linear model which best approximates the true nonlinear PWM amplifier. This work will look at the output response of the PWM amplifier with respect to stability and output ripple. A linear model will be developed which simulates these stability and ripple effects in a position control servo system and which is valid as system bandwidth reaches one-third the PWM switching frequency. This work extends the application of the Principle of Equivalent Areas [141 to the bipolar PWM amplifier. It is then combined with a detailed analysis of the PWM waveform by Double Fourier Transform to yield the unique PWM switching effects in a position control servo system. Theoretical results of the newly derived sampling plus harmonic linear model are verified by computer simulation

Motor Deficits Are Produced By Removing Some Cortical Transplants Grafted Into Injured Sensorimotor Cortex of Neonatal Rats

Fetal frontal cortex was transplanted into cavities formed in the right, motor cortex of neonatal rats. As adults, the animals were trained to press two levers in rapid succession with their left forelimb to receive food rewards. Once they had reached an optimal level of performance, the effect of removing their transplants was assessed. Surgical removal of transplants significantly impaired the performance of 2 of 4 subjects. Placing a crossstrain skin graft to induce the immunological rejection of the transplants produced a behavioral deficit in 1 of 2 subjects with complete transplant removal. Skin grafts produced no behavioral effects in four subjects that had surviving transplants. Since the motor deficit produced by transplant removal resembled those observed following the removal of normal motor cortex, we propose that these three transplants functioned within the host brain

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

Analysis of Shared Heritability in Common Disorders of the Brain

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology