Compensation Approach Research Articles

A receptance-based vibration control with dead-zone compensation for systems with input delay

This paper presents a novel compensation approach for receptance-based second-order systems with long input delay and unknown dead-zone input nonlinearity. The approach is based on a filtered Smith predictor for systems with long input delay based on the receptance model. An innovative discrete-time adaptive strategy approach for dealing with unknown input dead-zone is also based on a receptance model realization. The receptance-based second-order model is used on several fundamental applications, including active control vibration of mechanical vibrating systems. In the proposed approach, a filtered prediction error that considers the effects of time delay can be applied to pursue state feedback design for active vibration control purposes. The dead-zone compensation is treated by a discrete-time state observer, which is based on displacement, velocity, and control effort signals to estimate the unknown parameters to be used on an adaptive algorithm. The main contribution of this work is to combine unknown dead-zone adaptive mechanism and a receptance-based time delay compensation in a unified design. Some numerical examples illustrate the effectiveness of the innovative proposed approach.

Microfluidics Temperature Compensating and Monitoring Based on Liquid Metal Heat Transfer.

Microfluidic devices offer excellent heat transfer, enabling the biochemical reactions to be more efficient. However, the precision of temperature sensing and control of microfluids is limited by the size effect. Here in this work, the relationship between the microfluids and the glass substrate of a typical microfluidic device is investigated. With an intelligent structure design and liquid metal, we demonstrated that a millimeter-scale industrial temperature sensor could be utilized for temperature sensing of micro-scale fluids. We proposed a heat transfer model based on this design, where the local correlations between the macro-scale temperature sensor and the micro-scale fluids were investigated. As a demonstration, a set of temperature-sensitive nucleic acid amplification tests were taken to show the precision of temperature control for micro-scale reagents. Comparations of theoretical and experimental data further verify the effectiveness of our heat transfer model. With the presented compensation approach, the slight fluorescent intensity changes caused by isothermal amplification polymerase chain reaction (PCR) temperature could be distinguished. For instance, the probability distribution plots of fluorescent intensity are significant from each other, even if the amplification temperature has a difference of 1 °C. Thus, this method may serve as a universal approach for micro–macro interface sensing and is helpful beyond microfluidic applications.

Superpixel spectral unmixing framework for the volumetric assessment of tissue chromophores: A photoacoustic data-driven approach

The assessment of tissue chromophores at a volumetric scale is vital for an improved diagnosis and treatment of a large number of diseases. Spectral photoacoustic imaging (sPAI) co-registered with high-resolution ultrasound (US) is an innovative technology that has a great potential for clinical translation as it can assess the volumetric distribution of the tissue components. Conventionally, to detect and separate the chromophores from sPAI, an input of the expected tissue absorption spectra is required. However, in pathological conditions, the prediction of the absorption spectra is difficult as it can change with respect to the physiological state. Besides, this conventional approach can also be hampered due to spectral coloring, which is a prominent distortion effect that induces spectral changes at depth. Here, we are proposing a novel data-driven framework that can overcome all these limitations and provide an improved assessment of the tissue chromophores. We have developed a superpixel spectral unmixing (SPAX) approach that can detect the most and less prominent absorber spectra and their volumetric distribution without any user interactions. Within the SPAX framework, we have also implemented an advanced spectral coloring compensation approach by utilizing US image segmentation and Monte Carlo simulations, based on a predefined library of optical properties. The framework has been tested on tissue-mimicking phantoms and also on healthy animals. The obtained results show enhanced specificity and sensitivity for the detection of tissue chromophores. To our knowledge, this is a unique framework that accounts for the spectral coloring and provides automated detection of tissue spectral signatures at a volumetric scale, which can open many possibilities for translational research.

Credible commitments in contract relations: Where are the limits of the possible?

Credible commitments are the most important condition for contracts sustainability. The effects and ways of ensuring the commitments credibility are discussed in the new institutional economics and game theory. At the same time, there is a number of unresolved issues related to the microeconomic aspects of obligations’ reliability in contracts regarding specific resources. The article delves into various approaches to determining credible commitments in contractual relations at the micro level in the context of bilateral (multilateral) opportunism. The methodological basis of the study is the transaction costs economics. The paper shows the limitations of the compensation approach in modeling credible liabilities and explains the importance of relational credible commitments for ensuring sustainability and effectiveness of contracts. The author proposes an extended model of hostages in contracts using specific resources as a way of solving the “ugly princess” problem. Based on the specification of the temporal structure of contracting, we develop a game-theoretic model that takes into account the possibilities of opportunism on the part of both the pledger and the pledgee as an investor in specific assets. The study demonstrates the consequences of the wrong hostage chosen, as well as the characteristics of the interaction equilibrium due to the correct choice of it with an indication of the residual opportunism problem. The research provides a rationale why the promisee and the potential purchaser of full rights to an asset acting as a hostage are not always the same actor. The approaches to dealing with credible commitments in the context of renegotiations and multilateral contracts are outlined. The research results can serve as a basis for designing contracts requiring reciprocal collateral.

An Efficient Translational Motion Compensation Approach for ISAR Imaging of Rapidly Spinning Targets

For inverse synthetic aperture radar (ISAR) imaging of rapidly spinning targets, the large migration through range cells (MTRC) results in weak coherence between adjacent echoes, which makes the conventional envelope alignment method unable to be applied. By analyzing the correlation between the echoes, a translational motion compensation (TMC) method for rapidly spinning targets is proposed. Firstly, the rotation period of the target is estimated by the incoherent accumulation method for the echo signal after range compression. Secondly, Kalman filtering is performed on the shift values required to maximize the correlation coefficient of the echoes with one rotation period difference in azimuth time to obtain the relative translational motion of the radar and the target. Finally, a translational compensation function is constructed according to the results of Kalman filtering to compensate the phase items caused by translational motion. Furthermore, the covariance matrix of observation noise required by Kalman filtering is also provided. This method is used to achieve high-precision envelope alignment, and the effectiveness of the proposed method is validated by simulations.

Advanced part design method for springback minimization of stamped sheet metal car body components

The requirements for high-strength and low-weight car body structures prove challenging for the stamping process and cause growing problems with the elastic springback. Compensation approaches such as the geometrical adjustment of the stamping dies by the amount of and in opposite direction to the springback can be an effective solution in many cases. However, this approach can only lead to satisfactory results if the scatter of the springback is considered, controlled and in the best case reduced. The reduction of the scatter can be provoked by adaption of the part design. Therefore, different methods such as the topology optimization method, the so-called line-of-force method and shape optimization can be applied. In the present work an advanced topology optimization method is suggested. Based on the decomposition of the springback deformation into membrane and bending components, the most efficient optimization of the part design is found relying on unconventional topology optimization. For the proposed adapted topology optimization approach the excellent results are also confirmed when applied to the industry-relevant case of a truck rear panel.

Coupling 3D Liquid Simulation with 2D Wave Propagation for Large Scale Water Surface Animation Using the Equivalent Sources Method

AbstractThis paper proposes a method for simulating liquids in large bodies of water by coupling together a water surface wave simulator with a 3D Navier‐Stokes simulator. The surface wave simulation uses the equivalent sources method (ESM) to efficiently animate large bodies of water with precisely controllable wave propagation behavior. The 3D liquid simulator animates complex non‐linear fluid behaviors like splashes and breaking waves using off‐the‐shelf simulators using FLIP or the level set method with semi‐Lagrangian advection.We combine the two approaches by using the 3D solver to animate localized non‐linear behaviors, and the 2D wave solver to animate larger regions with linear surface physics. We use the surface motion from the 3D solver as boundary conditions for 2D surface wave simulator, and we use the velocity and surface heights from the 2D surface wave simulator as boundary conditions for the 3D fluid simulation. We also introduce a novel technique for removing visual artifacts caused by numerical errors in 3D fluid solvers: we use experimental data to estimate the artificial dispersion caused by the 3D solver and we then carefully tune the wave speeds of the 2D solver to match it, effectively eliminating any differences in wave behavior across the boundary. To the best of our knowledge, this is the first time such a empirically driven error compensation approach has been used to remove coupling errors from a physics simulator.Our coupled simulation approach leverages the strengths of each simulation technique, animating large environments with seamless transitions between 2D and 3D physics.

Convolutional Neural Network-Aided DP-64 QAM Coherent Optical Communication Systems

Optical nonlinearity impairments have been a major obstacle for high-speed, long-haul and large-capacity optical transmission. In this paper, we propose a novel convolutional neural network (CNN)-based perturbative nonlinearity compensation approach in which we reconstruct a feature map with two channels that rely on first-order perturbation theory and build a classifier and a regressor as a nonlinear equalizer. We experimentally demonstrate the CNN equalizer in 375 km 120-Gbit/s dual-polarization 64-quadrature-amplitude modulation (64-QAM) coherent optical communication systems. We studied the influence of the dropout value and nonlinear activation function on the convergence of the CNN equalizer. We measured the bit-error-ratio (BER) performance with different launched optical powers. When the channel size is 11, the optimum BER for the CNN classifier is 0.0012 with 1 dBm, and for the CNN regressor, it is 0.0020 with 0 dBm; the BER can be lower than the 7 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> hard decision-forward threshold of 0.0038 from −3 dBm to 3 dBm. When the channel size is 15, the BERs at −4 dBm, 4 dBm and 5 dBm can be lower than 0.0020. The network complexity is also analyzed in this paper. Compared with perturbative nonlinearity compensation using a fully connected neural network (2392-64-64), we can verify that the time complexity is reduced by about 25 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> , while the space complexity is reduced by about 50 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> .

Feedforward Model-Based Intelligent Compensation System for Spindle Dynamic Thermal Error

Among spindle dynamic errors, thermal error is an important factor affecting machining precision, the most convenient and economical solution for which is dynamic compensation of thermal error. In view of defects of complicated system, complex debugging, poor stability, high cost, etc., in the existing compensation approaches, thermal error compensation technology is investigated with compensation model established to complete the system design. The system is tested on the spindle of precise horizontal machining center. In the experiment, multiple linear regression, BP neural network, etc. are taken for technical analysis with dynamic feedforward model established. The experimental results indicate that the compensation system under study has dynamic compensation rate of over 90%, while the spindle has greatly shorter warm-up time, which can operate normally before entering the thermal steady state. The finally completed feedforward model-based intelligent compensation control system has good steady-state and dynamic compensation performance. In particular, its self-correction function greatly improves system adaptability and simplifies operation in use.

Advanced Contouring Compensation Approach via Newton-ILC and Adaptive Jerk Control for Biaxial Motion System

To achieve the precision contouring performance, this article presents a contouring compensation approach for the biaxial motion system even under extreme contour tasks. Two permanent magnet linear synchronous motors are installed in the biaxial motion platform. First, the dynamics of the biaxial motion servo system with the uncertainties such as model parameter variations, additive disturbance, and nonlinear friction are introduced. Since Newton algorithm is provided to realize dynamic contouring error estimation, accurate estimation of the contouring error can be achieved, even for the high velocity and complex contour with sharp corners and large curves. Then, iterative learning control (ILC) is used to control the contouring error for contouring performance improvement. An adaptive PD-type learning law based on an asymmetric Gaussian-like function is applied to improve the performance of the system. Moreover, adaptive jerk control (AJC) integrated with adaptive feedback gain is designed to address the negative effect of the uncertainties and enhance the robustness. The adaptive feedback gain is dominated and tuned by a novel adaptation law without the need for prior bound knowledge of the uncertainties. Meanwhile, parameter estimation is employed to handle the model parameter variations. Finally, the experimental results are presented to validate the efficiency and the achievable contouring performance of the proposed Newton-ILC and AJC approach.

Weak Grid-Induced Stability Problems and Solutions of Distributed Static Compensators with Voltage Droop Support

Distributed static compensators (DSTATCOMs) are grid-connected power electronic equipment dedicated to compensating reactive power as well as improving voltage regulation in distribution networks. They eclipse conventional compensation approaches, such as capacitor banks, in terms of flexibility and effectiveness. Despite their identified advantages, STATCOMs with voltage droop are subject to weak grid-induced stability problems, as first revealed by this paper. Specifically, the voltage droop controller that couples the amplitude of point of common coupling (PCC) voltages to the reactive current reference creates a local control loop. Such a loop greatly deteriorates system stability in weak grids, which feature large and variable grid impedances. To address such stability problems, we propose a novel virtual resistance control scheme, which improves system stability through mitigation of local control loop gains in the low-frequency band. Experimental results obtained from a DSTATCOM prototype clearly demonstrate the correctness of stability analysis and the effectiveness of stability improvement.

Targeted Deformable Motion Compensation for Vascular Interventional Cone-Beam CT Imaging.

Cone-beam CT has become commonplace for 3D guidance in interventional radiology (IR), especially for vascular procedures in which identification of small vascular structures is crucial. However, its long image acquisition time poses a limit to image quality due to soft-tissue deformable motion that hampers visibility of small vessels. Autofocus motion compensation has shown promising potential for soft-tissue deformable motion compensation, but it lacks specific target to the imaging task. This work presents an approach for deformable motion compensation targeted at imaging of vascular structures. The proposed method consists on a two-stage framework for: i) identification of contrast-enhanced blood vessels in 2D projection data and delineation of an approximate region covering the vascular target in the volume space, and, ii) a novel autofocus approach including a metric designed to promote the presence of vascular structures acting solely in the region of interest. The vesselness of the image is quantified via evaluation of the properties of the 3D image Hessian, yielding a vesselness filter that gives larger values to voxels candidate to be part of a tubular structure. A cost metric is designed to promote large vesselness values and spatial sparsity, as expected in regions of fine vascularity. A targeted autofocus method was designed by combining the presented metric with a conventional autofocus term acting outside of the region of interest. The resulting method was evaluated on simulated data including synthetic vascularity merged with real anatomical features obtained from MDCT data. Further evaluation was obtained in two clinical datasets obtained during TACE procedures with a robotic C-arm (Artis Zeego, Siemens Healthineers). The targeted vascular autofocus effectively restored the shape and contrast of the contrast-enhanced vascularity in the simulation cases, resulting in improved visibility and reduced artifacts. Segmentations performed with a single threshold value on the target vascular regions yielded a net increase of up to 42% in DICE coefficient computed against the static reference. Motion compensation in clinical datasets resulted in improved visibility of vascular structures, observed in maximum intensity projections of the contrast-enhanced liver vessel tree. Targeted motion compensation for vascular imaging showed promising performance for increased identification of small vascular structures in presence of motion. The development of autofocus metrics and methods tailored to vascular imaging opens the way for reliable compensation of deformable motion while preserving the integrity of anatomical structures in the image.

Range-Dependent Ambiguous Clutter Suppression for Airborne SSF-STAP Radar

Range-dependent clutter suppression is a challenging problem in nonsidelooking, bistatic, and conformal antenna array airborne radar, especially in the presence of range ambiguity. Superimposed stepped frequency (SSF) radar employs a small frequency increment across the stepped signals in each pulse, which introduces a dimension related to slant range. In this article, an airborne radar framework is established, which takes SSF signal as the transmit waveform. Thus, a two-stage adaptive clutter suppression method is proposed, which utilizes the degrees of freedom in range, space, and time domains provided by airborne SSF radar. In the first stage, the secondary range dependence compensation approach is adopted to distinguish the clutter of each range region in the carrier frequency domain. Then, a target-free covariance matrix is estimated by the compensated data, and the covariance matrix is used for the range-ambiguous clutter separation in the carrier frequency domain. Thus, the space-time snapshot of each range region can be extracted. In the second stage, a clutter segmentation processing method is devised for residual clutter suppression. For the near-range unambiguous clutter, the traditional clutter compensation approach is applied to further align the spectrum distribution of clutter, while the conventional space-time adaptive processing is utilized to suppress far-range clutter directly. Since the proposed method takes full advantage of the range dimension and the two stages of adaptive processing are data-dependent, excellent clutter suppression performance can be obtained. The proposed method can also extract the real range of the target since each range region is processed separately. Simulation results demonstrate the effectiveness of the proposed method.

Inversion-based attenuation compensation with dip constraint

Instability is an inherent problem with the attenuation compensation methods and has been partially relieved by using the inverse scheme. However, the conventional inversion-based attenuation compensation approaches ignore the important prior information of the seismic dip. Thus, the compensated result appears to be distorted spatial continuity and has a low signal-to-noise ratio (S/N). To alleviate this issue, we have incorporated the seismic dip information into the inversion framework and have developed a dip-constrained attenuation compensation (DCAC) algorithm. The seismic dip information, calculated from the poststack seismic data, is the key to construct a dip constraint term. Benefiting from the introduction of the seismic dip constraint, the DCAC approach maintains the numerical stability and preserves the spatial continuity of the compensated result. Synthetic and field data examples demonstrate that the proposed method can not only improve seismic resolution, but also protect the continuity of seismic data.

Robust Control of a Multi-Axis Shape Memory Alloy-Driven Soft Manipulator

Control of soft robotic manipulators remains a challenge for designs with advanced capabilities and novel actuation. Two significant limitations are multi-axis, three-dimensional motion of soft bodies alongside actuator dynamics and constraints, both of which are present in shape-memory-alloy (SMA)-powered soft robots. This article addresses both concerns with a robust feedback control scheme, demonstrating state tracking control for a soft robot manipulator of this type. Our controller uses a static beam bending model to approximate the soft limb as an LTI system, alongside a singular-value-decomposition compensator approach to decouple the multi-axial motion and an anti-windup element for the actuator saturation. We prove stability and verify robustness of our controller, with robustness intended to account for the unmodeled dynamics. Our implementation is verified in hardware trajectory tracking tests of a soft SMA-powered limb with accurate, promising results for future multi-limbed robots.

QCL-IR Spectroscopy for In-Line Monitoring of Proteins from Preparative Ion-Exchange Chromatography.

In this study, an external cavity-quantum cascade laser-based mid-infrared (IR) spectrometer was applied for in-line monitoring of proteins from preparative ion-exchange chromatography. The large optical path length of 25 μm allowed for robust spectra acquisition in the broad tuning range between 1350 and 1750 cm–1, covering the most important spectral region for protein secondary structure determination. A significant challenge was caused by the overlapping mid-IR bands of proteins and changes in the background absorption of water due to the NaCl gradient. Implementation of advanced background compensation strategies resulted in high-quality protein spectra in three different model case studies. In Case I, a reference blank run was directly subtracted from a sample run with the same NaCl gradient. Case II and III included sample runs with different gradient profiles than the one from the reference run. Here, a novel compensation approach based on a reference spectra matrix was introduced, where the signal from the conductivity detector was employed for correlating suitable reference spectra for correction of the sample run spectra. With this method, a single blank run was sufficient to correct various gradient profiles. The obtained IR spectra of hemoglobin and β-lactoglobulin were compared to off-line reference measurements, showing excellent agreement for all case studies. Moreover, the concentration values obtained from the mid-IR spectrometer agreed well with conventional UV detectors and high-performance liquid chromatography off-line measurements. LC–QCL–IR coupling thus holds high potential for replacing laborious and time-consuming off-line methods for protein monitoring in complex downstream processes.

Investigation of impedance compensation in radio frequency circuits with bonding wire

Bonding wires are extensively used to provide electrical interconnections in communication systems. From the perspective of circuit analysis, the effects of such elements are often treated as an inductance. Bonding wires may cause inductive impedance discontinuity, which negatively impacts signal integrity. In this work, an impedance compensation technique using a chip capacitor was introduced. The electrical performance was improved significantly in the frequency band below 4 GHz. In order to expand the operating frequency of the circuit, another compensation approach based on adding a ground conductor was also studied. This compensation strategy is shown to be effective for frequencies up to 18 GHz. The results obtained from the model simulation for both strategies were also validated experimentally. The model simulation results for both approaches show good agreement with those obtained from the experimental measurements.

Temperature Compensation of an Eddy-Current Displacement Sensor Using an Improved Sparrow Search Algorithm Method

Eddy-current displacement sensor (ECS) has been applied widely to the production of modern industry by reason of its characteristics of high sensitivity, good reliability, powerful anti-interference capacity, and noncontact measurement. However, it cannot be used when severe temperature drift occurs at high temperature. Some traditional compensation methods are difficult to achieve good performance with neglecting the nonlinearity. Hence, it is essential to propose a better method for temperature compensation. A novel temperature compensation approach for ECS problem using an improved sparrow search algorithm (ISSA) and radial basis function neural network (RBFNN) is proposed in this article. In the ISSA, a chaos strategy is introduced in the algorithm for avoiding local optimal point, and an elite opposition-based learning strategy is integrated to promote global search ability of ISSA with high efficiency. RBFNN is elected to model the temperature drift, and its parameters are determined by the proposed ISSA. The proposed method compensates the significant deterministic errors caused by temperature variation within a wide temperature range. The experimental schemes were designed to the effectiveness of the proposed method according to data fusion technology. The various test results obtained confirm the potential and effectiveness of the proposed approach compared to some other traditional temperature compensation methods presented in the literatures.

Influence and compensation of patient motion in electromagnetic tracking based quality assurance in interstitial brachytherapy of the breast.

Electromagnetic tracking (EMT) is a versatile and viable technique for various quality assurance (QA) tasks in interstitial brachytherapy (iBT). As the duration of EMT measurements in iBT is on the order of minutes, they can be strongly affected by patient motion, especially breathing, which gives rise to motion artefacts. Since the centrepiece of EMT-related QA in iBT is to assess the geometry of the iBT implant or applicator, the absence of adequate motion compensation techniques could impede the use of EMT for QA purposes. A common way to compensate for this is to reference the data to either external or internal reference sensors (ERS, IRS) which are fixated on the patient's body or inside the applicator and therefore move with the patient. The purpose of the presented study is to provide a quantitative and in-depth analysis on the use of reference sensors for motion compensation. First, the need for adequate motion compensation is identified both qualitatively and quantitatively using a phantom subjected to simulated breathing motion. An evaluation routine is developed to assess the influence of motion compensation using reference sensors on the acquired EMT data. The evaluation metric is based on the observed displacement of the EMT sensor from its mean position while dwelling at a dwell position (DP) for a dwell time of 1 s. After that, the routine is applied to a cohort of 54 breast cancer patients treated with iBT, and the quality of an ERS based compensation approach is assessed. In a subgroup of four patients, an IRS is inserted into the iBT implant and IRS-based compensation is compared to the ERS-based approach. Moreover, a correlation analysis of the ERS and IRS approach is performed, also including respiratory signals derived from the trajectories of the different reference sensors. It was found that motion compensation with ERS effectively reduced the mean sensor displacement per DP to median values as low as 0.11 mm in both phantom and patient measurements, which is below the precision of the EMT system (0.48 mm). Compensation using the IRS yielded comparable results and was as good as compensation with ERS. The results obtained from both approaches showed a strong correlation. Also the respiratory signals calculated from the different reference sensors were well correlated in most cases. These results indicate that motion compensation with ERS can effectively remove motion artefacts in EMT data. While compensation with an IRS leads to comparable results, the IRS occupies one catheter whose geometry hence cannot be assessed. The use of ERS has proven to be both effective and practical in clinical routine.

Neuroadaptive control of information-poor servomechanisms with smooth and nonsmooth uncertainties

For motion control of uncertain servomechanisms, nonlinear dynamics including smooth and nonsmooth types, external disturbances, signal measurement noises, asymmetric input saturation, and so on seriously hinder the further development of high-performance closed-loop control algorithms. However, already existing control strategies cannot address the above-mentioned issues at the same time. It greatly increases the difficulty of controller design especially when some states are not measurable. Inspired by above motivations, this paper exploits neural networks to deal with nonlinear dynamics including discontinuous types, and combines extended state observers to estimate disturbances and unmeasurable states for uncertain nonlinear servomechanisms. Meanwhile, the desired-command-based model compensation approach is integrated into the controller design. It is worth noting that the neural network weights are updated by the combination of the estimation error and tracking error to acquire better approximation accuracy. According to above technologies, a novel extended-state-observer-based neural network adaptive motion control algorithm will be synthesized. The bounded stability of the whole closed-loop system is proved strictly. In addition, the comparisons of the application results on an electro-hydraulic servo system verify the availability and superiority of the developed control algorithm.