Mismatch Errors Research Articles

Robust Control Examples Applied to a Wind Turbine Simulated Model

Wind turbine plants are complex dynamic and uncertain processes driven by stochastic inputs and disturbances, as well as different loads represented by gyroscopic, centrifugal and gravitational forces. Moreover, as their aerodynamic models are nonlinear, both modeling and control become challenging problems. On the one hand, high-fidelity simulators should contain different parameters and variables in order to accurately describe the main dynamic system behavior. Therefore, the development of modeling and control for wind turbine systems should consider these complexity aspects. On the other hand, these control solutions have to include the main wind turbine dynamic characteristics without becoming too complicated. The main point of this paper is thus to provide two practical examples of the development of robust control strategies when applied to a simulated wind turbine plant. Extended simulations with the wind turbine benchmark model and the Monte Carlo tool represent the instruments for assessing the robustness and reliability aspects of the developed control methodologies when the model-reality mismatch and measurement errors are also considered. Advantages and drawbacks of these regulation methods are also highlighted with respect to different control strategies via proper performance metrics.

Quadrature voltage control oscillator with a linear tuning law

New realisation scheme of linear voltage-controlled quadrature oscillator (QO) is proposed. The active building block is electronically tunable (ET) differential voltage current conveyor transconductance (gm) amplifier configured with current feedback amplifier and multiplication mode current conveyor devices. The designs are essentially tuned-inductor–capacitor oscillator, wherein the electronically variable lossless grounded inductor (L) had been simulated at suitable nodes of the active building block. Subsequently, with slight modification of the block, an ET floating-lossless immittance function generation is presented. Effects of device port mismatch error and parasitic capacitances are analysed. Albeit sensitivity relative to port mismatch error is negligible, the parasitic components tend to limit the higher-usable frequency range; appropriate design equations are derived for a true bilinear admittance function realisation and their applications to filter and sinusoid oscillator design are included. Experimental results on the QO with linear fo-tuning law are satisfactorily verified up to 8.7 MHz at low total harmonic distortion.

PN-assisted digital background calibration of two-step ADC to over 14-bit accuracy

A new non-binary multiplying digital-to-analog converter (MDAC) structure with signal-dependent dithering scaling technique is proposed in this paper. A full digital background calibration algorithm based on pseudo-random dithers injection is used to calibrate the nonlinear errors of MDAC. By measuring sampling capacitor mismatch and op-amp gain errors of the pipelined analog-to-digital converter (ADC) in background, the errors will be greatly reduced by the proposed calibration algorithm. At the same time, the signal-dependent dithering scaling technique provides a swing margin to the injected pseudo-random signal. By using this technique, the errors caused by the capacitor mismatch and op-amp gain errors can be calibrated at the same time. What’s more, this method greatly accelerates the convergence speed. A two-stage 14-bit pipelined ADC is used to simulate and verify the proposed algorithm. The simulation results indicate the effectiveness of the technique, in which the signal-to-noise plus distortion (SNDR) and the spurious-free dynamic range (SFDR) performance of a 14-bit two-step ADC are improved from 49.12 and 56.25 to 85.68 and 102.23 dB with the input frequency being 0.06 * f s , respectively. The SFDR is more than 98 dB. The SNDR reaches 84 dB in the whole Nyquist bandwidth after calibration. Integral nonlinearity is improved from 80 to 1.5 least significant bits after calibration.

Robust Beam-Tracking for mmWave Mobile Communications

We propose a robust beam-tracking algorithm to maintain the communication link between a base station (BS) and a mobile station (MS) in a millimeter wave mobile communications system, with antenna arrays at both the BS and MS. The channel is tracked with the extended Kalman filter (EKF) at the static BS and the beamforming weight is updated with a robust minimum mean squared error beamformer bounded by the array vector error which is fed from the error variance estimated by the EKF. Results show that our proposed method is able to maintain a link with the MS with a smaller mismatch error compared with existing beamtracking method at moderate MS mobility and antenna array size.

Reference-shaping adaptive control by using gradient descent optimizers.

This study presents a model reference adaptive control scheme based on reference-shaping approach. The proposed adaptive control structure includes two optimizer processes that perform gradient descent optimization. The first process is the control optimizer that generates appropriate control signal for tracking of the controlled system output to a reference model output. The second process is the adaptation optimizer that performs for estimation of a time-varying adaptation gain, and it contributes to improvement of control signal generation. Numerical update equations derived for adaptation gain and control signal perform gradient descent optimization in order to decrease the model mismatch errors. To reduce noise sensitivity of the system, a dead zone rule is applied to the adaptation process. Simulation examples show the performance of the proposed Reference-Shaping Adaptive Control (RSAC) method for several test scenarios. An experimental study demonstrates application of method for rotor control.

A Noninvasive Body Setup Method for Radiotherapy by Using a Multimodal Image Fusion Technique.

Purpose:To minimize the mismatch error between patient surface and immobilization system for tumor location by a noninvasive patient setup method.Materials and Methods:The method, based on a point set registration, proposes a shift for patient positioning by integrating information of the computed tomography scans and that of optical surface landmarks. An evaluation of the method included 3 areas: (1) a validation on a phantom by estimating 100 known mismatch errors between patient surface and immobilization system. (2) Five patients with pelvic tumors were considered. The tumor location errors of the method were measured using the difference between the proposal shift of cone-beam computed tomography and that of our method. (3) The collected setup data from the evaluation of patients were compared with the published performance data of other 2 similar systems.Results:The phantom verification results showed that the method was capable of estimating mismatch error between patient surface and immobilization system in a precision of <0.22 mm. For the pelvic tumor, the method had an average tumor location error of 1.303, 2.602, and 1.684 mm in left–right, anterior–posterior, and superior–inferior directions, respectively. The performance comparison with other 2 similar systems suggested that the method had a better positioning accuracy for pelvic tumor location.Conclusion:By effectively decreasing an interfraction uncertainty source (mismatch error between patient surface and immobilization system) in radiotherapy, the method can improve patient positioning precision for pelvic tumor.

Second‐order DAC MES for SAR ADCs

The successive approximation register (SAR) ADCs suffer from capacitor mismatch when considered for high-precision applications. Recently, a mismatch error shaping (MES) technique suitable for SAR ADCs has been proposed, by which the DAC mismatch error is first-order highpass shaped. The MES technique to the second-order is generalised. A concrete implementation of the second-order MES is presented. Theoretical analysis and simulations verify the feasibility and validity of the proposed technique. Compared to the previous one, the proposed second-order MES shows significantly improved shaping effect.

A Reduced Hardware ISI and Mismatch Shaping DEM Decoder

This paper presents a dynamic element matching (DEM) decoder incorporating both intersymbol interference (ISI) and mismatch error shaping. From the analysis of ISI error in multi-bit DACs, an algorithm is developed that deterministically controls the element transitions, such that on each conversion cycle the instantaneous number of on transitions is set to a constant value, while the instantaneous number of off transitions varies with the decoder input signal. The technique achieves greater ISI error mitigation than previous approaches using less hardware. To further reduce the logic area, a hierarchical DEM structure, whereby the DEM decoder is split into multiple sub-DEM decoders, is presented.

Sensorimotor impairment of speech auditory feedback processing in aphasia

We investigated the brain network involved in speech sensorimotor processing by studying patients with post-stroke aphasia using an altered auditory feedback (AAF) paradigm. We combined lesion-symptom-mapping analysis and behavioral testing to examine the pervasiveness of speech sensorimotor deficits and their relationship with cortical damage. Sixteen participants with aphasia and sixteen neurologically intact individuals completed a speech task under AAF. The task involved producing speech vowel sounds under the real-time pitch-shifted auditory feedback alteration. This task provided an objective measure for each individual's ability to compensate for mismatch (error) in speech auditory feedback. Results indicated that compensatory speech responses to AAF were significantly diminished in participants with aphasia compared with control. We observed that within the aphasic group, subjects with lower scores on the speech repetition task exhibited greater degree of diminished responses. Lesion-symptom-mapping analysis revealed that the onset phase (50–150 ms) of diminished AAF responses were predicted by damage to auditory cortical regions within the superior and middle temporal gyrus, whereas the rising phase (150–250 ms) and the peak (250–350 ms) of diminished AAF responses were predicted with damage to the inferior frontal gyrus and supramarginal gyrus areas, respectively. These findings suggest that damage to the auditory, motor, and auditory-motor integration networks are associated with impaired sensorimotor function for speech error processing. We suggest that a sensorimotor integration network, as revealed by brain regions related to temporal specific components of AAF responses, is related to speech processing and specific aspects of speech impairment, notably repetition deficits, in individuals with aphasia.

A 0.016 mm2 12 b $\Delta \Sigma $ SAR With 14 fJ/conv. for Ultra Low Power Biosensor Arrays

The instrumentation systems for implantable brain–machine interfaces represent one of the most demanding applications for ultra low-power analogue-to-digital-converters (ADC) to date. To address this challenge, this paper proposes a $\Delta \Sigma $ SAR topology for very large sensor arrays that allows an exceptional reduction in silicon footprint by using a continuous time 0–2MASH topology. This configuration uses a specialized FIR window to decimate the $\Delta \Sigma $ modulator output and reject mismatch errors from the SAR quantizer, which mitigates the overhead from dynamic element matching techniques commonly used to achieve high precision. A fully differential prototype was fabricated using $0.18\,\mu $ m CMOS to demonstrate 10.8 ENOB precision with a 0.016 mm2 silicon footprint. Moreover, a 14fJ/conv figure-of-merit can be achieved, while resolving signals with the maximum input amplitude of ±1.2 Vpp sampled at 200 kS/s. The ADC topology exhibits a number of promising characteristics for both high speed and ultra low-power systems due to the reduced complexity, switching noise, sampling load, and oversampling ratio, which are critical parameters for many sensor applications.

High-Resolution SAR ADC With Enhanced Linearity

This brief proposes two digital-to-analog converter switching techniques for binary-weighted capacitor array successive approximation register (SAR) analog-to-digital converter (ADC), rotating&averaging without redundancy technique and rotating&averaging with redundancy technique. The rotating&averaging without redundancy technique can improve the signal-to-noise ratio (SNR) and spurious free dynamic range (SFDR) of conventional SAR ADCs by averaging four samples for one input voltage, while the rotating&averaging with redundancy has better static linearity improvement but less SNR improvement than the rotating&averaging without redundancy technique. The application of these two methods to 14-bit SAR ADC is demonstrated by Monte-Carlo runs, results show that with a mismatch error typical of modern technology, the proposed rotating&averaging with redundancy scheme can improve the root-mean-square of integral nonlinearity from 2.08 to 0.57 LSB, and the SFDR is more than 15 dB better. On the other hand, the averaged SNR of 7.7 dB is improved by using the proposed rotating&averaging without redundancy technique for a 14-bit SAR ADC. Furthermore, the schemes proposed require only small additional circuit on a typical SAR ADC configuration, which are more feasible to implement high-resolution SAR ADC compared with the traditional calibration schemes.

Decentralized Dynamic Optimization for Power Network Voltage Control

Voltage control in power distribution networks has been greatly challenged by the increasing penetration of volatile and intermittent devices. These devices can also provide limited reactive power resources that can be used to regulate the network-wide voltage. A decentralized voltage control strategy can be designed by minimizing a quadratic voltage mismatch error objective using gradient-projection (GP) updates. Coupled with the power network flow, the local voltage can provide the instantaneous gradient information. This paper aims to analyze the performance of this decentralized GP-based voltage control design under two dynamic scenarios: i) the nodes perform the decentralized update in an asynchronous fashion, and ii) the network operating condition is time-varying. For the asynchronous voltage control, we improve the existing convergence condition by recognizing that the voltage based gradient is always up-to-date. By modeling the network dynamics using an autoregressive process and considering time-varying resource constraints, we provide an error bound in tracking the instantaneous optimal solution to the quadratic error objective. This result can be extended to more general \textit{constrained dynamic optimization} problems with smooth strongly convex objective functions under stochastic processes that have bounded iterative changes. Extensive numerical tests have been performed to demonstrate and validate our analytical results for realistic power networks.

All-Digital Calibration of Timing Mismatch Error in Time-Interleaved Analog-to-Digital Converters

This paper presents an all-digital background calibration for timing mismatch in time-interleaved analog-to-digital converters (TI-ADCs). It combines digital adaptive timing mismatch estimation and digital derivative-based correction, achieving lower hardware cost and better suppression of timing mismatch tones than previous work. In addition, for the first time closed-form exact expressions for the signal-to-noise and distortion ratio (SNDR) of a four-channel TI-ADC with timing mismatch after derivative-based digital correction are obtained, which can be used to guide the design. Simulation results of a four-channel TI-ADC behavioral model and measurement results from a commercial 12-bit 3.6-GS/s two-channel TI-ADC show that the proposed all-digital calibration can accurately estimate the timing skew and effectively correct the timing mismatch errors, while also confirming the analytic SNDR expressions.

An accurate algorithm for the detection of DNA fragments from dilution pool sequencing experiments.

The short read lengths of current high-throughput sequencing technologies limit the ability to recover long-range haplotype information. Dilution pool methods for preparing DNA sequencing libraries from high molecular weight DNA fragments enable the recovery of long DNA fragments from short sequence reads. These approaches require computational methods for identifying the DNA fragments using aligned sequence reads and assembling the fragments into long haplotypes. Although a number of computational methods have been developed for haplotype assembly, the problem of identifying DNA fragments from dilution pool sequence data has not received much attention. We formulate the problem of detecting DNA fragments from dilution pool sequencing experiments as a genome segmentation problem and develop an algorithm that uses dynamic programming to optimize a likelihood function derived from a generative model for the sequence reads. This algorithm uses an iterative approach to automatically infer the mean background read depth and the number of fragments in each pool. Using simulated data, we demonstrate that our method, FragmentCut, has 25-30% greater sensitivity compared with an HMM based method for fragment detection and can also detect overlapping fragments. On a whole-genome human fosmid pool dataset, the haplotypes assembled using the fragments identified by FragmentCut had greater N50 length, 16.2% lower switch error rate and 35.8% lower mismatch error rate compared with two existing methods. We further demonstrate the greater accuracy of our method using two additional dilution pool datasets. FragmentCut is available from https://bansal-lab.github.io/software/FragmentCut. vibansal@ucsd.edu. Supplementary data are available at Bioinformatics online.

Current Control of Grid-Connected Inverter With LCL Filter Based on Extended-State Observer Estimations Using Single Sensor and Achieving Improved Robust Observation Dynamics

In the context of distributed generation and renewable energy penetration toward smart grid, grid-connected inverter with LCL filter has drawn many attentions, whose current control conventionally requires several sensors to realize active damping and grid synchronization. In this paper, a novel full status observation strategy based on extended state observer (ESO) is proposed using inverter current feedback only and without grid voltage sensor. The proposed observation strategy contains observation and transformation process. Unlike conventional Luenberger observer, by using ESO, the system parameters do not appear in observation process, thus the observer dynamics and parameter mismatch error can be separately handled, providing more robust observation dynamics during parameter variation. Parameter mismatch study was carried out, and it is found that purposely choosing the observer parameters smaller than the real value can achieve relatively low estimation error and a large adaption range for parameter variation. The proposed observation strategy is simple to implement, without the need of expert knowledge-based parameter tuning such as pole placement. Experimental tests validated that the proposed observation-based control is able to give satisfactory performance in both dynamic and steady states, as well as adaption for system parameter variation.

A Complex Least Squares Enhanced Smart DFT Technique for Power System Frequency Estimation

A complex-valued least-squares (CLS) framework is proposed in order to enhance the accuracy of the smart discrete Fourier transform (SDFT) algorithms for power system frequency estimation in the presence of noise and harmonic pollution. It is first established that the underlying time-series relationship among the consecutive DFT fundamental components employed by the original SDFT algorithms does not hold when noises or unexpected higher order harmonics are present, resulting in suboptimal estimation performances. To eliminate these adverse effects on the frequency estimation, the degree of the relationship breakdown is next quantified via a model mismatch error vector. The CLS technique is then employed to minimize the mean-square model deviation when the SDFT voltage modelling is suboptimal. The proposed CLS-enhanced SDFT (CLS-SDFT) methods are shown to be more accurate than the original ones in heavily noisy and harmonic-distorted environments, typical scenarios in online frequency estimation. The benefits of the SDFT framework are verified by simulations for various power system conditions, as well as for real-world measurements.

Wide‐band high‐accuracy ΔΣ ADC using segmented DAC with DWA and mismatch shaping

A discrete-time ΔΣ analogue-to-digital converter utilising a multi-bit successive approximation register quantiser and a segmented digital-to-analogue converter (DAC) is proposed. By adding the delayed DAC output to the modulator input and removing it at the modulator output in the digital domain, the mismatch error is filtered. Thus, a first-order DAC mismatch error shaping is realised. This improves the DAC linearity without introducing an extra delay in the feedback path. Segmenting the DAC and processing the least significant bit and most significant bit segments separately, the dynamic range remains unaffected.

Electronically Tunable Dual-Input Integrator: Synthetic Immittance Function Realizability

ABSTRACTA new electronically tunable differential input integrator (ETDII) using the composite current feedback amplifier (CFA) and multiplication-mode current conveyor (MMCC) building block is presented, wherein the control voltage (Vc) of the MMCC tunes its time constant (τ). Effects of the device parasitic capacitances had been examined and appropriate compensation design is proposed to obtain high-quality (q) realization. Analysis shows that τ is practically active insensitive to device port mismatch errors (ϵ). A quadrature voltage controlled oscillator (VCO) is implemented utilizing the ETDII after suitably configuring a double-integrator loop with grounded capacitors in the same topology. With the loop closed, the ETDII topology realizes some new electronically tunable synthetic immittance function at appropriate nodes. Satisfactory experimental results for the proposed realizations had been verified with PSPICE macro-model simulation and by hardware test.

How do specimen preparation and crystal perfection affect structure factor measurements by quantitative convergent-beam electron diffraction?

The effectiveness of tripod polishing and crushing as methods of mechanically preparing transmission electron microscopy specimens of hard brittle inorganic crystalline materials is investigatedviathe example of cerium hexaboride (CeB6). It is shown that tripod polishing produces very large electron-transparent regions of very high crystal perfection compared to the more rapid technique of crushing, which produces crystallites with a high density of imperfections and significant mosaicity in the case studied here where the main crystallite facets are not along the natural {001} cleavage planes of CeB6. The role of specimen quality in limiting the accuracy of structure factor measurements by quantitative convergent-beam electron diffraction (QCBED) is investigated. It is found that the bonding component of structure factors refined from CBED patterns obtained from crushed and tripod-polished specimens varies very significantly. It is shown that tripod-polished specimens yield CBED patterns of much greater integrity than crushed specimens and that the mismatch error that remains in QCBED pattern matching of data from tripod-polished specimens is essentially nonsystematic in nature. This stands in contrast to QCBED using crushed specimens and lends much greater confidence to the accuracy and precision of bonding measurements by QCBED from tripod-polished specimens.

Skill Transfer Between Industrial Robots by Learning from Demonstration

Industrial robots are the key role in modern manufacture. In order to allow different robots to perform the same task, they must be programmed manually which is time-consuming and cumbersome. The ability to transfer robotic skills between heterogeneous robots would provide significances to industry. This paper presents a prototype control architecture for industrial robots which allows multiple heterogeneous robots of different morphologies to perform the same task without manually programming each robot separately. We selected three articulated industrial manipulators with different degree of freedoms (Yaskawa Motoman HP3JC: 6, Universal Robot UR5: 6 and Rethink Robotics Baxter: 7) to test our approach. Two simple tasks were chosen for implementation and analysis. Results indicate that our approach works with some errors. Maximum and average position mismatch errors for UR5 are 4.9380 cm and 4.4761 cm. For Baxter, maximum and average position mismatch errors are 1.7770 cm and 1.6068 cm. Baxter has a different range of motion therefore some places could not be reached with it.