On low-pass reconstruction and stochastic modeling of PWM signals

Mathematical modeling of pulse width modulation (PWM) is given. For a band-limited, finite energy input signal, a PWM generation mechanism is investigated in linear and non-linear blocks separately. Following the common practice, a comparator block with a periodic reference signal is offered as a PWM generator and different sampling methodologies are discussed. For natural sampling, where the input signal is compared to the reference signal directly, lossless sampling conditions are derived. For a sawtooth reference signal, the convergence characteristics between lossless natural sampling and uniform sampling, where a zero-order hold (ZOH) block precedes the comparator, are analyzed. For a given input model, the convergence characteristics are tested with simulations and signal to absolute deviation energy for the difference between natural and uniform sampling is observed for different oversampling levels. Motivated by the separation of linear and non-linear blocks in PWM generation, a similar method for the analysis at the reconstruction end is pursued. In this pursuit, continuous-time low-pass filtering, preceded by oversampling, is analyzed as a linear suboptimal reconstruction mechanism from a PWM signal. Observing the mapping between input samples and pulse widths, an infinite energy, input-independent, structural component of a PWM signal is revealed. Manipulating the linear nature of the low-pass filtering, and equivalent model is proposed to analyze the finite energy, input-dependent component of the PWM signal separately. Frequency domain analysis for fixed-edge and double-edge PWM orientations and their corresponding input-dependent components are given. Using the frequency domain representations, performance bounds for low-pass reconstruction of a band-limited, finite energy input signal are derived and fundamental trade-offs between generator complexity and distortion attenuation capacity are revealed. Stochastic modeling of PWM processes for independent identically distributed (i.i.d.) pulse widths is discussed. For a fixed starting model of a PWM process, the violation of wide sense stationarity (WSS) is observed. By introducing a randomized starting point, independent of the pulse widths and uniformly distributed over a symbol interval, a WSS PWM process is constructed and its stochastic characteristics are analyzed. For i.i.d. uniform pulse widths, second moments are simulated revealing a smoothing effect in the double-edge PWM construction, consistent to the frequency domain analysis

Parameter Identification And Fault Detection For Reliable Control Of Permanent Magnet Motors

The objective of this dissertation is to develop new fault detection, identification, estimation and control algorithms that will be used to detect winding stator fault, identify the motor parameters and optimally control machine during faulty condition. Quality or proposed algorithms for Fault detection, parameter identification and control under faulty condition will validated through analytical study (Cramer-Rao bound) and simulation. Simulation will be performed for three most applied control schemes: Proportional-Integral-Derivative (PID), Direct Torque Control (DTC) and Field Oriented Control (FOC) for Permanent Magnet Machines. New detection schemes forfault detection, isolation and machine parameter identification are presented and analyzed. Different control schemes as PID, DTC, FOC for Control of PM machines have different control loops and therefore it is probable that fault detection and isolation will have different sensitivity. It is very probable that one of these control schemes (PID, DTC or FOC) are more convenient for fault detection and isolation which this dissertation will analyze through computer simulation and, if laboratory condition exist, also running a physical models

Measuring reproducibility of high-throughput experiments

Reproducibility is essential to reliable scientific discovery in high-throughput experiments. In this work we propose a unified approach to measure the reproducibility of findings identified from replicate experiments and identify putative discoveries using reproducibility. Unlike the usual scalar measures of reproducibility, our approach creates a curve, which quantitatively assesses when the findings are no longer consistent across replicates. Our curve is fitted by a copula mixture model, from which we derive a quantitative reproducibility score, which we call the "irreproducible discovery rate" (IDR) analogous to the FDR. This score can be computed at each set of paired replicate ranks and permits the principled setting of thresholds both for assessing reproducibility and combining replicates. Since our approach permits an arbitrary scale for each replicate, it provides useful descriptive measures in a wide variety of situations to be explored. We study the performance of the algorithm using simulations and give a heuristic analysis of its theoretical properties. We demonstrate the effectiveness of our method in a ChIP-seq experiment.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS466 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Real Time Estimation, Quantization, And Remote Control Of Permanent Magnet Dc Motors

Establishing real-time models for electric motors is of importance for capturing authentic dynamic behavior of the motors to improve control performance, enhance robustness, and support diagnosis. Quantized sensors are less expensive and remote controlled motors mandate signal quantization. Such limitations on observations introduce challenging issues in motor parameter estimation. This dissertation develops estimators for model parameters of permanent magnet direct current motors (PMDC) using quantized speed measurements. A typical linearized model structure of PMDC motors is used as a benchmark platform to demonstrate the technology, its key properties, and benefits. Convergence properties are established. Simulations and experimental studies are performed to illustrate potential applications of the technology. Remotely-controlled Permanent Magnet DC (PMDC) motors must transmit speed measurements and receive control commands via communication channels. Sampling, quantization, data transfer, and signal reconstruction are mandatory in such networked systems, and introduce additional dynamic subsystems that substantially affect feedback stability and performance. The intimate interaction among sampling periods, signal estimation step sizes, and feedback dynamics entails careful design considerations in such systems. This dissertation investigates the impact of these factors on PMDC motor performance, by rigorous analysis, simulation case studies, and design trade-off examination. The findings of this dissertation will be of importance in providing design guidelines for networked mobile systems, such as autonomous vehicles, mobile sensors, unmanned aerial vehicles which often use electric motors as main engines

Interference Characterization in Multiple Access Wireless Networks

Contrarily to the point to point wireless link approach adopted in several wireless networks, where a dedicated channel is usually supporting an exclusive-use wireless link, in the last years several wireless communication systems have followed a different approach. In the so called “multiple access wireless networks”, multiple transmitters share the same communication channel in a simultaneous way, supporting a shared-use of the wireless link. The deployment of multiple access networks has also originated the emergence of various communication networks operating in the same geographical area and spectrum space, which is usually referred to as wireless coexistence. As a consequence of the presence of multiple networks with different technologies that share the same spectral bands, robust methods of interference management are needed. At the same time, the adoption of in-band Full-duplex (IBFDX) communication schemes, in which a given node transmit and receive simultaneously over the same frequency band, is seen as a disruptive topic in multiple access networks, capable of doubling the network’s capacity. Motivated by the importance of the interference in multiple access networks, this thesis addresses new approaches to characterize the interference in multiple access networks. A special focus is given to the assumption of mobility for the multiple transmitters. The problem of coexistence interference caused by multiple networks operating in the same band is also considered. Moreover, given the importance of the residual self-interference (SI) in practical IBFDX multiple access networks, we study the distribution of the residual SI power in a wireless IBFDX communication system. In addition, different applications of the proposed interference models are presented, including the definition of a new sensing capacity metric for cognitive radio networks, the performance evaluation of wireless-powered coexisting networks, the computation of an optimal carrier-sensing range in coexisting CSMA networks, and the estimation of residual self-interference in IBFDX communication systems