Richard Kielbasa

Capacitive detection scheme for space accelerometers applications

Abstract This paper presents the design and performance of an ultra-sensitive position sensor dedicated to future space accelerometers. The electromechanical transducer is based on a capacitive scheme and aims at detecting the motion of a proof-mass in an electrostatic accelerometer. A new design called “area variation capacitance” is investigated to minimize back-action forces exerted on the proof mass. The resolution of that position sensor is a few tenths of picometer in the 0–1 Hz bandwidth. The position is digitized with a sigma–delta converter to feed the control laws of the accelerometer.

Latin Hypercube Sampling Monte Carlo Estimation of AverageQuality Index for Integrated Circuits

The Monte Carlo method exhibits generality and insensitivityto the number of stochastic variables, but is expensive for accurateAverage Quality Measure (AQI) or Parametric Yield estimationof MOS VLSI circuits. In this contribution a new method of variancereduction technique, viz. the Latin Hypercube Sampling (LHS)method is presented which improves the efficiency of AQI estimationin integrated circuits especially for MOS digital circuits. Thismethod is similar to the Primitive Monte Carlo (PMC) methodexcept in samples generation step where the Latin Hypercube Samplingmethod is used. This sampling method is very simple and doesnot involve any further simulations. Moreover, it has a smallervariance with respect to the PMC estimator. Encouraging resultshave thus far been obtained. A 3-dimensional quadratic function,a high pass filter, and a CMOS delay circuit examples are includedto demonstrate the efficiency of this technique.

Synthesis and Analysis of Sigma-Delta Modulators Employing Continuous-Time Filters

A methodology for analysis and synthesis of lowpass sigma-delta (ΣΔ) converters is presented in this paper. This method permits the synthesis of ΣΔ modulators employing continuous-time filters from discrete-time topologies. The analysis method is based on the discretization of a continuous-time model and using a discrete simulator, which is more efficient than an analog simulator. In our analysis approach, the influence of the sample and hold block and non-idealities of the feedback DAC can be systematically modeled by discrete-time systems. Finally, a realistic design of a second-order ΣΔ modulator with a compensation of the non-ideal behavior of the DAC is given. Moreover, simulation results show a good agreement with the theoretical predictions.

Modified Latin Hypercube Sampling Monte Carlo (MLHSMC) Estimation for Average Quality Index

The Monte Carlo (MC) method exhibits generality and insensitivity to the number of stochastic variables, but it is expensive for accurate Average Quality Index (AQI) or Parametric Yield estimation of MOS VLSI circuits or discrete component circuits. In this paper a variant of the Latin Hypercube Sampling MC method is presented which is an efficient variance reduction technique in MC estimation. Theoretical and practical aspects of its statistical properties are also given. Finally, a numerical and a CMOS clock driver circuit examples are given. Encouraging results and good agreement between theory and simulation results have thus far been obtained.

A digital piezoelectric accelerometer with sigma-delta servo technique

Abstract This paper presents the design and performance of a direct digital accelerometer using oversampling sigma-delta servo electronics. The measuring system, also called an ‘electromechanical sigma-delta modulator’, is based on a piezoelectric measuring cell integrated inside the first stage of a second-order sigma-delta modulator. The piezoelectric measuring cell has a new structure in order to realize the acceleration sensing and the servo-loop summer. The active material used in an inexpensive and versatile piezoelectric polymer, polyvinylidene fluoride (PVDF). The accelerometer aims at a working range of ± 1 g and eight-bit resolution. It is suited for vibration measurement.

A Matlab based tool for bandpass continuous-time sigma-delta modulators design

A methodology for synthesis and analysis of bandpass sigma-delta (/spl Sigma//spl Delta/) converters has been developed and integrated in a Matlab toolbox. It allows the synthesis of /spl Sigma//spl Delta/ modulators with continuous time filters from discrete time topologies. The analysis method is based on the discretization of continuous-time models. It uses a discrete time simulator, more efficient than an analog simulator. All tools are included in a fully interactive, graphic and open framework in which user-developed modules can be added.

A study of stratified sampling in variance reduction techniques for parametric yield estimation

In the literature, several variance reduction techniques in Monte Carlo circuit yield estimation have been described, e.g., stratified sampling. In this contribution the theoretical aspects of partitioning scheme of the tolerance region in stratified sampling is presented. To the best of our knowledge, this problem was not previously studied in parametric yield estimator. The proposed stratified sampling Monte Carlo yield estimator has always a smaller or equal variance with respect to Primitive Monte Carlo (PMC) yield estimator.

A passive delta-sigma modulator for low-power applications

This paper demonstrates at the transistor level that sigma-delta modulators using passive filters can be good candidates for low power applications. The circuit we propose is composed of a latch-type self-timed comparator, a switched capacitor passive filter and a voltage reference with an additive dithering signal. Time-domain simulations show that 10-bit resolutions can be expected with usual over-sampling ratio values. The enhancement provided by dither noise is highlighted. The global current consumption is below 10 /spl mu/A for a 1 MHz sampling frequency.

Resolution Enhancement of a Sigma-Delta Micro-Accelerometer Using Signal Prediction

This paper presents a new design of a closed-loop sigma-delta accelerometer using an acceleration prediction feedback element. Thanks to a Kalman state estimator associated with a Linear-Quadratic-Gaussian (LQG) controller, the proof mass is maintained near its position of equilibrium. Consequently, operating on the relatively small proof mass displacement makes it possible to enhance the performance of the sigma-delta converter. This architecture shows an increase of more than 20 dB in signal quantization noise ratio compared to conventional sigma-delta accelerometers and has the advantage of being a completely digital solution.

ESTIMATION OF EXTREME VALUES, WITH APPLICATION TO UNCERTAIN SYSTEMS

Extreme events are defined as extreme high (or low) values of whatever statistics of the output of the system we are interested in. These values play an important role because they may correspond to abnormal or dangerous operating conditions. Classical statistical inference techniques provide a good description of central behaviour, but not of extreme events. This was our motivation for resorting to extreme-value theory, which provides a framework and tools to model these extreme events. We show in this paper how some of these tools can be used in the context of system reliability, and the resulting methodology is illustrated on an example of circuit design, representative of a wide new field of applications for extreme-value theory.