Reliability Analysis on Repairable System with Dual Input Closed-Loop Feedback Link Considering Shutdown Correlation Based on Goal Oriented Methodology

Goal oriented( GO) methodology is a kind of success oriented system reliability analysis method and has been used widely.The repairable system with dual input closed-loop feedback link( DICLFL) considering shutdown correlation didn't make reliability analysis accurately based on existing GO methodology. So, a reliability analysis method used to deal with DICLFL considering shutdown correlation is provided based on GO methodology.Firstly, a new operator, which is used to describe DICLFL considering shutdown correlation,whose number is 1,is created and named as Type 9C operator. And then,the formulas of type 9C operator are derived based on Markov process theory. Finally,the new method presented in this paper is adopted to conduct the reliability analysis of an electro-hydraulic servo speed control system. The analysis result is compared with those of Monte Carlo simulation and fault tree analysis( FTA). The comparison results show that this new reliability analysis method based on GO methodology is feasible and meaningful for reliability analysis of repairable systems with DICLFL considering shutdown correlation.Meantime,it will be useful for more other applications.

Reliability Analysis of Repairable System with Multiple Closed-Loop Feedbacks Based on GO Method

In order to solve the problem of reliability modeling and the analysis of complex systems with multiple closed-loop feedbacks,a new reliability analysis method for repairable systems with multiple closed-loop feedbacks is proposed based on the goal-oriented(GO)methodology.Firstly,the basic theories and advantages of GO method are introduced.Secondly,a type-24B multiple closed-loop feedback structure operator is proposed through GO method with its operation formula given,which expands the types of GO method operators and the application scope of their reliability analysis.Finally,taking a certain type of diesel engine fuel supply system an example,the quantitative and qualitative analysis is carried out through GO method,Monte Carlo simulation as well as FTA respectively.The availability results verify the availability of the proposed type-24B operator in the reliability analysis of multiple closed-loop feedback systems.The qualitative analysis results indicate the accuracy and usability of the GO method as a qualitative analysis method.

A feedback control method for phase signal demodulation in fber-optic hydrophones

In the realm of acoustic signal detection,the identification of weak signals,particularly in the presence of negative signal-to-noise ratios,poses a significant challenge.This challenge is further heightened when signals are acquired through fiber-optic hydrophones,as these signals often lack physical significance and resist clear systematic modeling.Conventional processing methods,e.g.,low-pass filter(LPF),require a thorough understanding of the effective signal bandwidth for noise reduction,and may introduce undesirable time lags.This paper introduces an innovative feedback control method with dual Kalman filters for the demodulation of phase signals with noises in fiber-optic hydrophones.A mathematical model of the closed-loop system is established to guide the design of the feedback control,aiming to achieve a balance with the input phase signal.The dual Kalman filters are instrumental in mitigating the effects of signal noise,observation noise,and control execution noise,thereby enabling precise estimation for the input phase signals.The effectiveness of this feedback control method is demonstrated through examples,showcasing the restoration of low-noise signals,negative signal-to-noise ratio signals,and multi-frequency signals.This research contributes to the technical advancement of high-performance devices,including fiber-optic hydrophones and phase-locked amplifiers.

Fault Estimation for a Class of Markov Jump Piecewise-Affine Systems: Current Feedback Based Iterative Learning Approach

In this paper, the issues of stochastic stability analysis and fault estimation are investigated for a class of continuoustime Markov jump piecewise-affine(PWA) systems against actuator and sensor faults. Firstly, a novel mode-dependent PWA iterative learning observer with current feedback is designed to estimate the system states and faults, simultaneously, which contains both the previous iteration information and the current feedback mechanism. The auxiliary feedback channel optimizes the response speed of the observer, therefore the estimation error would converge to zero rapidly. Then, sufficient conditions for stochastic stability with guaranteed performance are demonstrated for the estimation error system, and the equivalence relations between the system information and the estimated information can be established via iterative accumulating representation.Finally, two illustrative examples containing a class of tunnel diode circuit systems are presented to fully demonstrate the effectiveness and superiority of the proposed iterative learning observer with current feedback.

A Tutorial on Quantized Feedback Control

In this tutorial paper, we explore the field of quantized feedback control, which has gained significant attention due to the growing prevalence of networked control systems. These systems require the transmission of feedback information, such as measurements and control signals, over digital networks, presenting novel challenges in estimation and control design. Our examination encompasses various topics, including the minimal information needed for effective feedback control, the design of quantizers, strategies for quantized control design and estimation,achieving consensus control with quantized data, and the pursuit of high-precision tracking using quantized measurements.

Towards engineering a portable platform for laparoscopic pre-training in virtual reality with haptic feedback

Background Laparoscopic surgery is a surgical technique in which special instruments are inserted through small incision holes inside the body.For some time,efforts have been made to improve surgical pre training through practical exercises on abstracted and reduced models.Methods The authors strive for a portable,easy to use and cost-effective Virtual Reality-based(VR)laparoscopic pre-training platform and therefore address the question of how such a system has to be designed to achieve the quality of today's gold standard using real tissue specimens.Current VR controllers are limited regarding haptic feedback.Since haptic feedback is necessary or at least beneficial for laparoscopic surgery training,the platform to be developed consists of a newly designed prototype laparoscopic VR controller with haptic feedback,a commercially available head-mounted display,a VR environment for simulating a laparoscopic surgery,and a training concept.Results To take full advantage of benefits such as repeatability and cost-effectiveness of VR-based training,the system shall not require a tissue sample for haptic feedback.It is currently calculated and visually displayed to the user in the VR environment.On the prototype controller,a first axis was provided with perceptible feedback for test purposes.Two of the prototype VR controllers can be combined to simulate a typical both-handed use case,e.g.,laparoscopic suturing.A Unity based VR prototype allows the execution of simple standard pre-trainings.Conclusions The first prototype enables full operation of a virtual laparoscopic instrument in VR.In addition,the simulation can compute simple interaction forces.Major challenges lie in a realistic real-time tissue simulation and calculation of forces for the haptic feedback.Mechanical weaknesses were identified in the first hardware prototype,which will be improved in subsequent versions.All degrees of freedom of the controller are to be provided with haptic feedback.To make forces tangible in the simulation,characteristic values need to be determined using real tissue samples.The system has yet to be validated by cross-comparing real and VR haptics with surgeons.

A chaotic hierarchical encryption/watermark embedding scheme for multi-medical images based on row-column confusion and closed-loop bi-directional diffusion

Security during remote transmission has been an important concern for researchers in recent years.In this paper,a hierarchical encryption multi-image encryption scheme for people with different security levels is designed,and a multiimage encryption(MIE)algorithm with row and column confusion and closed-loop bi-directional diffusion is adopted in the paper.While ensuring secure communication of medical image information,people with different security levels have different levels of decryption keys,and differentiated visual effects can be obtained by using the strong sensitivity of chaotic keys.The highest security level can obtain decrypted images without watermarks,and at the same time,patient information and copyright attribution can be verified by obtaining watermark images.The experimental results show that the scheme is sufficiently secure as an MIE scheme with visualized differences and the encryption and decryption efficiency is significantly improved compared to other works.

Evaluation of hybrid closed-loop insulin delivery system in type 1 diabetes in real-world clinical practice:One-year observational study

BACKGROUND In 2016,the Food and Drug Administration approved the first hybrid closed-loop(HCL)insulin delivery system for adults with type 1 diabetes(T1D).There is limited information on the impact of using HCL systems on patient-reported outcomes(PROs)in patients with T1D in real-world clinical practice.In this independent study,we evaluated glycemic parameters and PROs over one year of continuous use of Medtronic’s 670G HCL in real-world clinical practice.AIM To assess the effects of hybrid closed loop system on glycemic control and quality of life in adults with T1D.METHODS We evaluated 71 patients with T1D(mean age:45.5±12.1 years;59%females;body weight:83.8±18.7 kg,body mass index:28.7±5.6 kg/m2,A1C:7.6%±0.8%)who were treated with HCL at Joslin Clinic from 2017 to 2019.We measured A1C and percent of glucose time-in-range(%TIR)at baseline and 12 months.We measured percent time in auto mode(%TiAM)for the last two weeks preceding the final visit and assessed PROs through several validated quality-of-life surveys related to general health and diabetes management.RESULTS At 12 mo,A1C decreased by 0.3%±0.1%(P=0.001)and%TIR increased by 8.1%±2.5%(P=0.002).The average%TiAM was only 64.3%±32.8%and was not associated with A1C,%TIR or PROs.PROs,provided at baseline and at the end of the study,showed that the physical functioning submodule of 36Item Short-Form Health Survey increased significantly by 22.9%(P<0.001).Hypoglycemia fear survey/worry scale decreased significantly by 24.9%(P<0.000);Problem Areas In Diabetes reduced significantly by-17.2%(P=0.002).The emotional burden submodules of dietary diversity score reduced significantly by-44.7%(P=0.001).Furthermore,analysis of Clarke questionnaire showed no increase in awareness of hypoglycemic episodes.WHO-5 showed no improvements in subject’s wellbeing among participants after starting the 670G HCL system.Finally,analysis of Pittsburgh Sleep Quality Index showed no difference in sleep quality,sleep latency,or duration of sleep from baseline to 12 mo.CONCLUSION The use of HCL in real-world clinical practice for one year was associated with significant improvements in A1C,%TIR,physical functioning,hypoglycemia fear,emotional distress,and emotional burden related to diabetes management.However,these changes were not associated with time in auto mode.

Adaptive Optimal Discrete-Time Output-Feedback Using an Internal Model Principle and Adaptive Dynamic Programming

In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization problem. We then design an observer to reproduce the full state of the system by measuring the inputs and outputs. Moreover, this technique includes both a policy iteration algorithm and a value iteration algorithm to determine the optimal feedback gain without using a dynamic system model. It is important that with this concept one does not need to solve the regulator equation. Finally, this control method was tested on an inverter system of grid-connected LCLs to demonstrate that the proposed method provides the desired performance in terms of both tracking and disturbance rejection.

The Effectiveness of Peer Feedback on Second Language Writing

Peer feedback is a widely utilized practice in writing classrooms for second languages(L2)that has drawn a lot of attention.While some support the practice because of the clear advantages that peer feedback offers students,others doubt its efficacy.Comparing various forms of feedback is therefore necessary,as is determining the effects that peer feedback has on students and the variables that might affect how successful peer feedback is.This paper focuses on the usefulness of peer feedback for L2 writing,based on a review of studies on the subject.The findings imply that the functions of peer and teacher feedback are distinct,and that peer feedback is advantageous to both parties,particularly to the supplier.The attitudes and cultural backgrounds of the students are among the other factors that affect how effective peer feedback is.Lastly,some implications for future research and education are presented.

A Fully Differential Interface Circuit of Closed-loop Accelerometer with Force Feedback Linearization

In this paper,a fifth-order fully differential interface circuit( IC) is presented to improve the noise performance for micromechanical sigma-delta( Σ-Δ) accelerometer. A lead compensator is adopted to ensure the stability of the closed-loop high-order system. A low noise capacitance detection circuit is described with a correlated-double-sampling( CDS) technique to decrease 1 /f noise and offset of the operational amplifier. This paper also proposes a self-test technique for the interface circuit to test the harmonic distortion. An electrostatic force feedback linearization circuit is presented to reduce the harmonic distortion resulting in larger dynamic range( DR). The layout of the IC is implemented in a standard 0. 6 μm CMOS technology and operates at a sampling frequency of 250 kHz. The interface consumes 20 mW from a 5 V supply. The post-simulation results indicate that the noise floor of the digital accelerometer is about- 140 dBV /Hz1 /2at low frequency. The sensitivity is 2. 5 V /g and the nonlinearity is 0. 11%. The self-test function is achieved with 98. 2 dB thirdorder harmonic distortion detection based on the electrostatic force feedback linearization.

The Representation of Soil Moisture−Atmosphere Feedbacks across the Tibetan Plateau in CMIP6

Thermal processes on the Tibetan Plateau(TP)influence atmospheric conditions on regional and global scales.Given this,previous work has shown that soil moisture−driven surface flux variations feed back onto the atmosphere.Whilst soil moisture is a source of atmospheric predictability,no study has evaluated soil moisture−atmosphere coupling on the TP in general circulation models(GCMs).In this study,we use several analysis techniques to assess soil moisture−atmosphere coupling in CMIP6 simulations including:instantaneous coupling indices;analysis of flux and atmospheric behaviour during dry spells;and a quantification of the preference for convection over drier soils.Through these metrics we partition feedbacks into their atmospheric and terrestrial components.Consistent with previous global studies,we conclude substantial inter-model differences in the representation of soil moisture−atmosphere coupling,and that most models underestimate such feedbacks.Focusing on dry spell analysis,most models underestimate increased sensible heat during periods of rainfall deficiency.For example,the model-mean bias in anomalous sensible heat flux is 10 W m−2(≈25%)smaller compared to observations.Deficient dry-spell sensible heat fluxes lead to a weaker atmospheric response.We also find that most GCMs fail to capture the negative feedback between soil moisture and deep convection.The poor simulation of feedbacks in CMIP6 experiments suggests that forecast models also struggle to exploit soil moisture−driven predictability.To improve the representation of land−atmosphere feedbacks requires developments in not only atmospheric modelling,but also surface processes,as we find weak relationships between rainfall biases and coupling indexes.

Research on Narrowband Line Spectrum Noise Control Method Based on Nearest Neighbor Filter and BP Neural Network Feedback Mechanism

Thefilter-x least mean square(FxLMS)algorithm is widely used in active noise control(ANC)systems.However,because the algorithm is a feedback control algorithm based on the minimization of the error signal variance to update thefilter coefficients,it has a certain delay,usually has a slow convergence speed,and the system response time is long and easily affected by the learning rate leading to the lack of system stability,which often fails to achieve the desired control effect in practice.In this paper,we propose an active control algorithm with near-est-neighbor trap structure and neural network feedback mechanism to reduce the coefficient update time of the FxLMS algorithm and use the neural network feedback mechanism to realize the parameter update,which is called NNR-BPFxLMS algorithm.In the paper,the schematic diagram of the feedback control is given,and the performance of the algorithm is analyzed.Under various noise conditions,it is shown by simulation and experiment that the NNR-BPFxLMS algorithm has the following three advantages:in terms of performance,it has higher noise reduction under the same number of sampling points,i.e.,it has faster convergence speed,and by computer simulation and sound pipe experiment,for simple ideal line spectrum noise,compared with the convergence speed of NNR-BPFxLMS is improved by more than 95%compared with FxLMS algorithm,and the convergence speed of real noise is also improved by more than 70%.In terms of stability,NNR-BPFxLMS is insensitive to step size changes.In terms of tracking performance,its algorithm responds quickly to sudden changes in the noise spectrum and can cope with the complex control requirements of sudden changes in the noise spectrum.

Effects of Different Feedback Conditions on Sensorimotor Adaptation Revealed in a Mirror Reversal Paradigm

Humans are able to overcome sensory perturbations imposed on their movements through motor learning. One of the key mechanisms to accomplish this is sensorimotor adaptation, an implicit, error-driven learning mechanism. Past work on sensorimotor adaptation focused mainly on adaptation to rotated visual feedback—A paradigm known as visuomotor rotation. Recent studies have shown that sensorimotor adaptation can also occur under mirror-reversed visual feedback. In visuomotor rotation, sensorimotor adaptation can be driven by both endpoint and online feedback [1] [2]. However, it’s not been clear whether both kinds of feedback can similarly drive adaptation under a mirror reversed perturbation. We performed a study to establish what kinds of feedback can drive adaptation under mirror reversal. In the first two conditions, the participants were asked to ignore visual feedback. In the first condition, we provided mirror reversed online feedback and endpoint feedback. We reproduced previous findings showing that online feedback elicited adaptation under mirror reversal. In a second condition, we provided mirror reversed endpoint feedback. However, in the second condition, we found that endpoint feedback alone failed to elicit adaptation. In a third condition, we provided both types of feedback at the same time, but in a conflicting way: endpoint feedback was non-reversed while online feedback was mirror reversed. The participants were asked to ignore online visual feedback and try to hit the target with help from veridical endpoint feedback. In the third condition, in which veridical endpoint feedback and mirror reversed online feedback were provided, adaptation still occurred. Our results showed that endpoint feedback did not elicit adaptation under mirror reversal but online feedback did. This dissociation between effects of endpoint feedback and online feedback on adaptation under mirror reversal suggests that adaptation under these different kinds of feedback might in fact operate via distinct mechanisms.

A compact and closed-loop spin-exchange relaxation-free atomic magnetometer for wearable magnetoencephalography

Atomic magnetometers operated in the spin-exchange relaxation-free(SERF)regime are the promising sensor to replace superconducting quantum interference devices(SQUIDs)in the biomagnetism field.The SERF magnetometer with compact size and good performance is crucial to the new generation of wearable magnetoencephalography(MEG)system.In this paper,we developed a compact and closed-loop SERF magnetometer with the dimensions of 15.0×22.0×30.0 mm^(3)based on a single-beam configuration.The bandwidth of the magnetometer was extended to 675 Hz while the sensitivity was maintained at 22 f T/Hz^(1/2).A nearly 3-fold enhancement of the bandwidth was obtained in comparison with the open-loop control.The implementation of the closed-loop control also greatly improved the dynamic range,enabling the magnetometer to be robust against the disturbance of the ambient field.Moreover,the magnetometer was successfully applied for the detection of humanα-rhythm and auditory evoked fields(AEFs),which demonstrated the potential to be extended to multi-channel MEG measurements for future neuroscience studies.

Subspace Identification for Closed-Loop Systems With Unknown Deterministic Disturbances

This paper presents a subspace identification method for closed-loop systems with unknown deterministic disturbances.To deal with the unknown deterministic disturbances,two strategies are implemented to construct the row space that can be used to approximately represent the unknown deterministic disturbances using the trigonometric functions or Bernstein polynomials depending on whether the disturbance frequencies are known.For closed-loop identification,CCF-N4SID is extended to the case with unknown deterministic disturbances using the oblique projection.In addition,a proper Bernstein polynomial order can be determined using the Akaike information criterion(AIC)or the Bayesian information criterion(BIC).Numerical simulation results demonstrate the effectiveness of the proposed identification method for both periodic and aperiodic deterministic disturbances.

A multi-module with a two-way feedback method for Ulva drift-diffusion

The outbreak of Ulva in the Yellow Sea has seriously affected marine ecology and economic activities.Therefore,effective prediction of the distribution of Ulva is of great significance for disaster prevention and reduction.However,the prediction method of Ulva is mainly based on numerical simulation.There are two problems with these methods.First is that the initial distribution of Ulva is simulated using independent pixel-level particles.Besides,the influence of Ulva growth and diffusion on the drift is not considered.Therefore,this paper proposes a multi-module with a two-way feedback method(MTF)to solve the above problems.The main contributions of our approach are summarized as follows.First,the initialization module,the generation and elimination module,and the drive module are composed in our way.Second,we proposed an initialization method using rectangle objects to simulate the Ulva distribution extracted from remote sensing images.Thirdly,the drift and diffusion mechanism of the Ulva is considered to realize the two-way feedback between the generation and elimination module and the drive module.The results of our experiments show that the MTF performs better than the traditional method in predicting the drift and diffusion of Ulva.The code is already publicly available at https://github.com/UPCGIT/A-multi-module-with-a-two-way-feedback-method-for-Ulva-drift-diffusion.

Type Synthesis of Fully Decoupled Three Translational Parallel Mechanism with Closed-Loop Units and High Stifness

In order to solve the problem of weak stifness of the existing fully decoupled parallel mechanism, a new synthesis method of fully decoupled three translational (3T) parallel mechanisms (PMs) with closed-loop units and high stifness is proposed based on screw theory. Firstly, a new criterion for the full decoupled of PMs is presented that the reciprocal product of the transmission wrench screw matrix and the output twist screw matrix of PMs is a diagonal matrix, and all elements on the main diagonal are nonzero constants. The forms of the transmission wrench screws are determined by the criterion. Secondly, the forms of the actuated and unactuated screws can be obtained according to their relationships with the transmission wrench screws. The basic decoupled limbs are generated by combination of the above actuated and unactuated screws. Finally, a closed-loop units construction method is investigated to apply the decoupled mechanisms in a better way on the high stifness occasion. The closed-loop units are constructed in the basic decoupled limbs to generate a high-stifness fully decoupled 3T PM. Kinematic and stifness analyses show that the Jacobian matrix is a diagonal matrix, and the stifness is obviously higher than that of the coupling mechanisms, which verifes the correctness of the proposed synthesis method. The mechanism synthesized by this method has a good application prospect in vehicle durability test platform.

Fuzzy Feedback Control for Electro-Hydraulic Actuators

Electro-hydraulic actuators(EHA)have recently played a significant role in modern industrial applications,especially in systems requiring extremely high precision.This can be explained by EHA’s ability to precisely control the position and force through advanced sensors and innovative control algorithms.One of the promising approaches to improve control accuracy for EHA systems is applying classical to modern control algorithms,in which the proportional–inte-gral–derivative(PID)algorithm,fuzzy logic controller,and a hybrid of these methods are popular options.In this paper,we developed a novel version of the fuzzy control algorithm and linear feedback control method,namely fuzzy lin-ear feedback control,to improve the control performance.To achieve the highest performance,wefirst designed a mathematical EHA model based on the Matlab/Simulink software packages thanks to the selected parameters,which are similar to a real EHA system.Then,we respectively applied PID,fuzzy PID(FPID),and fuzzy linear feedback control(FLFC)before comparing them to have a full view of the outstanding advantages of the proposed algorithm.The simulation results showed that the proposed FLFC algorithm is approximately 99%and 77%super-ior in performance to the PID and feedback control algorithms,respectively.

A novel zero-payload downlink CSI feedback scheme for closed-loop beamforming system

A novel downlink channel state information(CSI)feedback scheme is proposed for the closed-loopbeamforming system.In the proposed scheme,mobile terminal(MT)superposes the uplink pilot on thereceived downlink pilot,forms the hybrid pilot(HP),and then transmits the HP to base station(BS)viathe uplink pilot channel.Because downlink CSI can be recovered from HP at BS side without consumingextra uplink bandwidth,the proposed scheme can achieve zero-payload CSI feedback,effectively solvingthe traditional bottleneck problems,i.e.,the heavy burden for transmitting CSI.Moreover,both MT'scomplexity and feedback delays can be reduced since the downlink channel needs not to be estimated atMT any more.Simulations verify that the proposed scheme can achieve the better MSE performance forthe uplink channel estimation than the traditional scheme,and the cost for the zero-payload CSI feedbackis some acceptable loss of feedback precision.