Variable Feedback Research Articles

Coquaternions, Metric Invariants of Biologic Systems and Malignant Transformations

Different hypotheses of carcinogenesis have been proposed based on local genetic factors and physiologic mechanisms. It is assumed that changes in the metric invariants of a biologic system (BS) determine the general mechanisms of cancer development. Numerous pieces of data demonstrate the existence of three invariant feedback patterns of BS: negative feedback (NFB), positive feedback (PFB) and reciprocal links (RL). These base patterns represent basis elements of a Lie algebra sl(2,R) and an imaginary part of coquaternion. Considering coquaternion as a model of a functional core of a BS, in this work a new geometric approach has been introduced. Based on this approach, conditions of the system are identified with the points of three families of hypersurfaces in R42: hyperboloids of one sheet, hyperboloids of two sheets and double cones. The obtained results also demonstrated the correspondence of an indefinite metric of coquaternion quadratic form with negative and positive entropy contributions of the base elements to the energy level of the system. From that, it can be further concluded that the anabolic states of the system will correspond to the points of a hyperboloid of one sheet, whereas catabolic conditions correspond to the points of a hyperboloid of two sheets. Equilibrium states will lie in a double cone. Physiologically anabolic and catabolic states dominate intermittently oscillating around the equilibrium. Deterioration of base elements increases positive entropy and causes domination of catabolic states, which is the main metabolic determinant of cancer. Based on these observations and the geometric representation of a BS’s behavior, it was shown that conditions related to cancer metabolic malfunction will have a tendency to remain inside the double cone.

Model predictive control–based compound control strategy for ducted rockets gas flow with anti-regulation suppression

Variable flow ducted rockets are excellent candidates for propulsion systems in hypersonic vehicles. However, the anti-regulation characteristics of the gas flow not only decrease the stability of ducted rockets but also create difficulties in the control system design. In this study, a model predictive control (MPC)–based compound control algorithm that suppresses the anti-regulation is proposed. First, a mathematical model involving a gas flow regulation system was developed to describe and analyse the anti-regulation. Next, a fused feedback variable that included both the gas flow and the gas generator pressure signal was constructed. An MPC control system with the fused feedback variable was also designed. Then, to accurately predict the gas flow and the anti-regulation, a nonlinear disturbance observer was constructed. To evaluate the performance of the controller, two scenarios that were regulated by a tracking differentiator proportional–integral–derivative controller and a model reference adaptive control controller were constructed and compared. The theoretical results demonstrate that the proposed method exhibited a superior performance compared to previous methods by overcoming the supposed trade-off between the response rate and the anti-regulation of gas flow systems.

Toward Minimal Data Rate Enforcing Regular Safety Properties: An Invariance Entropy Approach

The study of minimal data rate for control using some notions of entropy has been so far limited to classical control tasks such as set invariance, state-estimation, or stabilization. In this work, for the first time, we present a study on sufficient data rates to enforce regular safety properties over uncertain systems with dynamics described by set valued maps. Every regular safety property has a set of bad prefixes which can be modelled by a deterministic finite automaton (DFA). The main idea is to construct a hybrid system by taking the product of the deterministic finite automata with the given system and studying the invariance feedback entropy (IFE) of controlled invariant sets of the hybrid system. If there exists a nonempty controlled invariant set for the hybrid system satisfying a certain property then there exists a coder-controller with a data rate not less than the IFE that can enforce the regular safety property over the original control system. We demonstrate the effectiveness of our results by designing a coder-controller enforcing a regular safety property over a linear control system.

Closed-Loop Control of a Multifunctional Myoelectric Prosthesis With Full-State Anatomically Congruent Electrotactile Feedback.

State-of-the-art myoelectric hand prostheses provide multi-functional control but lack somatosensory feedback. To accommodate the full functionality of a dexterous prosthesis, the artificial sensory feedback needs to convey several degrees of freedom (DoF) simultaneously. However, this is a challenge with current methods as they are characterized by a low information bandwidth. In this study, we leverage the flexibility of a recently developed system for simultaneous electrotactile stimulation and electromyography (EMG) recording to present the first solution for closed-loop myoelectric control of a multifunctional prosthesis with full-state anatomically congruent electrotactile feedback. The novel feedback scheme (coupled encoding) conveyed proprioceptive (hand aperture, wrist rotation) and exteroceptive information (grasping force). The coupled encoding was compared to the conventional approach (sectorized encoding) and incidental feedback in 10 non-disabled and one amputee participant who used the system to perform a functional task. The results showed that both feedback approaches increased the accuracy of position control compared to incidental feedback. However, the feedback increased completion time, and it did not significantly improve grasping force control. Importantly, the performance of the coupled feedback was not significantly different compared to the conventional scheme, despite the latter being easier to learn during training. Overall, the results indicate that the developed feedback can improve prosthesis control across multiple DoFs but they also highlight the subjects' ability to exploit minimal incidental information. Importantly, the current setup is the first to convey three feedback variables simultaneously using electrotactile stimulation while providing multi-DoF myoelectric control with all hardware components mounted on the same forearm.

The Moderating Role of Feedback on the Effect of Goal-Setting Participation on Innovative Work Behaviour

Change is something that is bound to happen. Employees in service industries such as hospitality business must have innovative work behavior to help companies grow and thrive in a constantly changing environment. One way to get employee work integrity in the face of change is to set work goals. The involvement of employees in setting work goals is inseparable from the role of superiors to provide feedback. This study aims to describe the relationship between goal-setting participation and employees' innovative work behavior and their relationship with feedback as a moderating variable. The research methodology uses a quantitative descriptive approach, whereas 101 of four-star hotel employees in Belitung Regency and employed convenience sampling. The results revealed that goal-setting variable has a positive and meaningful relationship with the feedback variable. Moreover, the feedback variable has a role both as an independent and a moderator variable in the relationship between goal-setting variable and innovative work behavior. The implications of the research results provide input to hotel business actors the importance of encouraging goal-setting participation and employing the goals as the positive feedback for the employees.

Distributed Model Reference Adaptive Control Based on Cooperative Observer with Optimal Control Modification for Synchronization of Heterogeneous Vehicle Platoon

Many distributed controllers for vehicle platoon are designed based on homogeneous assumption and full state information. In reality, vehicle platoon may consist of heterogeneous vehicles and may have limited information due to sensor constraints. Therefore, this paper proposes a distributed model reference adaptive control based on cooperative observer for a heterogeneous vehicle platoon with limited output information and subjected to uncertain dynamics. Cooperative observer provides a full state estimation of the system. Each follower has a reference model that is designed based on its nominal model and cooperative state variable feedback. Main control system is composed of (i) nominal control that utilized the cooperative state estimation tracking error and (ii) adaptive term that adopted an optimal control modification as an adaptation law. The tracking error of followers to the reference model is shown uniformly bounded and the stability of the platoon is guaranteed through detailed analysis. Performance of the proposed controller is verified by using numerical simulation. To show the advantage of the proposed control, simulation results are compared to the standard distributed model reference adaptive control that is applied for heterogeneous vehicle platoon. It is shown that the proposed control eliminated the high frequency oscillation in the control input.

"Maybe it's the first time somebody's been honest with you": exploring how residents reconcile feedback variability.

Supervisors in postgraduate medical education may deliver different feedback for the same quality of performance. Residents may struggle to make sense of inconsistent and sometimes contradictory information. We sought to explore how residents experience feedback from different supervisors, how they process inconsistent information, and what factors influence their experiences. Eighteen residents participated in semi-structured interviews to explore their perspectives on feedback. Using a constructivist grounded theory approach, we engaged in iterative cycles of data collection and analysis, sampling until theoretical sufficiency was reached. Constant comparative analysis was used to identify and define themes. We identified a central theme of reconciliation, which we defined as the act of processing inconsistent feedback and determining how to engage with it. This reconciliation was informed by the credibility of, and residents' relationship with, supervisors and was achieved through conversations with peers and mentors, observation of other supervisors' behavior toward their performance, and reflection on their own performance. Participants expressed a reluctance to discard feedback, even if they felt it was incongruent with previous feedback or their own self-concept and self-assessment. The findings of this study show that while residents are regular consumers of feedback, not all feedback is used equally. Residents actively reconcile sometimes-contradictory feedback and must work to balance a general reluctance to discard feedback, while developing an understanding of its credibility. This work reinforces the importance of pedagogical relationships and identifies that facilitated reflection that explicitly acknowledges feedback inconsistencies may be important in the reconciliation process.

Fringe Detection and Displacement Sensing for Variable Optical Feedback-Based Self-Mixing Interferometry by Using Deep Neural Networks

Laser feedback-based self-mixing interferometry (SMI) is a promising technique for displacement sensing. However, commercial deployment of such sensors is being held back due to reduced performance in case of variable optical feedback which invariably happens due to optical speckle encountered when sensing the motion of non-cooperative remote target surfaces. In this work, deep neural networks have been trained under variable optical feedback conditions so that interferometric fringe detection and corresponding displacement measurement can be achieved. We have also proposed a method for automatic labelling of SMI fringes under variable optical feedback to facilitate the generation of a large training dataset. Specifically, we have trained two deep neural network models, namely Yolov5 and EfficientDet, and analysed the performance of these networks on various experimental SMI signals acquired by using different laser-diode-based sensors operating under different noise and speckle conditions. The performance has been quantified in terms of fringe detection accuracy, signal to noise ratio, depth of modulation, and execution time parameters. The impact of network architecture on real-time sensing is also discussed.

Observed and CMIP6 Modeled Internal Variability Feedbacks and Their Relation to Forced Climate Feedbacks

AbstractInter model variations in global temperature response to increasing atmospheric carbon dioxide stem mostly from uncertainties in modeled climate feedbacks. To study potential reductions in model feedback uncertainties, we estimate observed feedbacks in response to internal variability using changes in Top Of the Atmosphere energy balance with temperature. We compare those observations with internal variability feedbacks from historical simulations of coupled and atmosphere‐only experiments from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to identify that simulated feedbacks exhibit biases in the tropics, subtropics, and the Southern Ocean. Furthermore, we find a relation between simulated longwave and shortwave internal variability feedbacks and those where atmospheric carbon dioxide is abruptly quadrupled. In the model range of internal variability feedbacks, the observations are more consistent with moderately negative longwave feedback, and weak shortwave feedback, but the observations can't be used to rule out any models or their long‐term feedback.

Exploring surface electromyography (EMG) as a feedback variable for the human-in-the-loop optimization of lower limb wearable robotics.

Human-in-the-loop (HITL) optimization with metabolic cost feedback has been proposed to reduce walking effort with wearable robotics. This study investigates if lower limb surface electromyography (EMG) could be an alternative feedback variable to overcome time-intensive metabolic cost based exploration. For application, it should be possible to distinguish conditions with different walking efforts based on the EMG. To obtain such EMG data, a laboratory experiment was designed to elicit changes in the effort by loading and unloading pairs of weights (in total 2, 4, and 8 kg) in three randomized weight sessions for 13 subjects during treadmill walking. EMG of seven lower limb muscles was recorded for both limbs. Mean absolute values of each stride prior to and following weight loading and unloading were used to determine the detection rate (100% if every loading and unloading is detected accordingly) for changing between loaded and unloaded conditions. We assessed the use of multiple consecutive strides and the combination of muscles to improve the detection rate and estimated the related acquisition times of diminishing returns. To conclude on possible limitations of EMG for HITL optimization, EMG drift was evaluated during the Warmup and the experiment. Detection rates highly increased for the combination of multiple consecutive strides and the combination of multiple muscles. EMG drift was largest during Warmup and at the beginning of each weight session. The results suggest using EMG feedback of multiple involved muscles and from at least 10 consecutive strides (5.5 s) to benefit from the increases in detection rate in HITL optimization. In combination with up to 20 excluded acclimatization strides, after changing the assistance condition, we advise exploring about 16.5 s of walking to obtain reliable EMG-based feedback. To minimize the negative impact of EMG drift on the detection rate, at least 6 min of Warmup should be performed and breaks during the optimization should be avoided. Future studies should investigate additional feedback variables based on EMG, methods to reduce their variability and drift, and should apply the outcomes in HITL optimization with lower limb wearable robots.

Modeling simulation and inverter control strategy research of microgrid in grid-connected and island mode

Under the “double carbon” goal, distributed generation (DG) with inverters will show an explosive growth trend. The microgrid can operate in different modes as a channel for DG to connect to the main grid. In the microgrid, the fast response characteristics of power electronics exacerbate the instability of the microgrid when switching between grid-connected and islanded modes. On the PSCAD/EMTDC simulation platform, a refined power generation model with wind–solar–load–storage microgrid is built to capture the behavior of the system, rather than using a highly simplified model. At the same time, a reasonable control strategy is necessary, which is the key to maintaining the stability of the system. Existing control strategies can only operate in a single mode or the control effect is not ideal. Based on this, on the basis of droop control, the virtual adaptive control loop is added in this study, and the virtual impedance value is adaptively changed according to different output conditions to achieve the purpose of precise control; In the active power control loop, the frequency signal is drawn from the phase-locked loop, and becomes a power feedback variable through the signal transformation process, thereby participating in the power control process and improving the accuracy of frequency control. A standard microgrid power generation model and an inverter control model suitable for grid-connected and off-grid microgrids are built, and the voltage and frequency fluctuations in the two modes are analyzed to verify the effectiveness of the strategy.

Hardware Efficient Hybrid Pseudo-Random Bit Generator Using Coupled-LCG and Multistage LFSR with Clock Gating Network

A new method for the generation of pseudo-random bits, based on a coupled-linear congruential generator (CLCG) and two multistage variable seeds linear feedback shift registers (LFSRs) is presented. The proposed algorithm dynamically changes the value of the seeds of each linear congruential generator (LCG) by utilizing the multistage variable seeds LFSR. The proposed approach exhibits several advantages over the pseudo-random bit generator (PRBG) methods presented in the literature. It provides low hardware complexity and high-security strength while maintaining the minimum critical path delay. Moreover, this design generates the maximum length of pseudo-random bit sequence with uniform clock latency. Furthermore, to improve the critical path delay, one more architecture of PRBG is proposed in this work. It is based on the combination of coupled modified-LCG with two variable seeds multistage LFSRs. The modified LCG block is designed by the two-operand modulo adder and XOR gate, rather than the three-operands modulo adder and shifting operation, while it maintains the same security strength. The clock gating network (CGN) is also used in this work to minimize the dynamic power dissipation of the overall PRBG architecture. The proposed architectures are implemented using Verilog HDL and further prototyped on commercially available field-programmable gate array (FPGA) devices Virtex-5 and Virtex-7. The realization of the proposed architecture in this FPGA device accomplishes an improved speed of PRBG, which consumes low power with high randomness compared to existing techniques. The generated binary sequence from the proposed algorithms has been verified for randomness tests using NIST statistical test suites.

A Double-Side Feedback Pulse Train Control for the Output Voltage Regulation of Two-Stage Wireless Power Transfer System

Pulse Train (PT) control is a nonlinear voltage regulation method with favorable characteristics of quick response time and simple structure. In this paper, a PT-based feedback control strategy is proposed for stabilizing the output voltage of two-stage wireless power transfer (WPT) systems. Low-frequency voltage oscillations can be observed in PT controlled front-stage power converters, which significantly degrades the output power quality of the WPT system. To solve this problem, by using feedback variables sampled from both output sides of a power converter and WPT, a capacitor current and output voltage feedback PT (CC&OV-PT) controlled two-stage WPT system is further devised in this paper. A discrete time model of the two-stage WPT system is established, and the performance of low-frequency voltage oscillations suppression for the double-side feedback CC&OV-PT controlled WPT system is analyzed. Simulation and experimental verification have been conducted, both of which show that the CC&OV-PT controlled WPT system achieves fast response with effective low-frequency oscillation suppression.

Synchronization in a multilevel network using the Hamilton-Jacobi-Bellman (HJB) technique.

This paper presents the optimal control and synchronization problem of a multilevel network of Rössler chaotic oscillators. Using the Hamilton-Jacobi-Bellman technique, the optimal control law with a three-state variable feedback is designed such that the trajectories of all the Rössler oscillators in the network are optimally synchronized at each level. Furthermore, we provide numerical simulations to demonstrate the effectiveness of the proposed approach for the cases of one and three networks. A perfect correlation between the MATLAB and PSpice results was obtained, thus allowing the experimental validation of our designed controller and shows the effectiveness of the theoretical results.

Active Damping Control for LCL Filters With Inverter-Side Current Feedback Only

In the past decade, extensive active damping solutions based on state variable feedback have been proposed to damp <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LCL</i> resonance. In this letter, an innovative control strategy, which can achieve overcurrent protection, injected power control, and active damping at the same time, is proposed with the inverter-side current feedback only. Moreover, to avoid the mathematical limitations when solving characteristic roots of a third-order system, the damping-factor-based design method is proposed for the first time, by analyzing its equivalent circuit. The optimal damping factor, which is recommended to be positive and as large as possible, is searched to achieve superior resonance suppression effect. Finally, the proposed control and design method is verified by experimental results and shows good robustness both in stiff and ultraweak grid conditions.

Optimization of a Quality Improvement Tool for Cancer Diagnosis in Primary Care: Qualitative Study.

BackgroundThe most common route to a diagnosis of cancer is through primary care. Delays in diagnosing cancer occur when an opportunity to make a timely diagnosis is missed and is evidenced by patients visiting the general practitioner (GP) on multiple occasions before referral to a specialist. Tools that minimize prolonged diagnostic intervals and reduce missed opportunities to investigate patients for cancer are therefore a priority.ObjectiveThis study aims to explore the usefulness and feasibility of a novel quality improvement (QI) tool in which algorithms flag abnormal test results that may be indicative of undiagnosed cancer. This study allows for the optimization of the cancer recommendations before testing the efficacy in a randomized controlled trial.MethodsGPs, practice nurses, practice managers, and consumers were recruited to participate in individual interviews or focus groups. Participants were purposively sampled as part of a pilot and feasibility study, in which primary care practices were receiving recommendations relating to the follow-up of abnormal test results for prostate-specific antigen, thrombocytosis, and iron-deficiency anemia. The Clinical Performance Feedback Intervention Theory (CP-FIT) was applied to the analysis using a thematic approach.ResultsA total of 17 interviews and 3 focus groups (n=18) were completed. Participant themes were mapped to CP-FIT across the constructs of context, recipient, and feedback variables. The key facilitators to use were alignment with workflow, recognized need, the perceived importance of the clinical topic, and the GPs’ perception that the recommendations were within their control. Barriers to use included competing priorities, usability and complexity of the recommendations, and knowledge of the clinical topic. There was consistency between consumer and practitioner perspectives, reporting language concerns associated with the word cancer, the need for more patient-facing resources, and time constraints of the consultation to address patients’ worries.ConclusionsThere was a recognized need for the QI tool to support the diagnosis of cancer in primary care, but barriers were identified that hindered the usability and actionability of the recommendations in practice. In response, the tool has been refined and is currently being evaluated as part of a randomized controlled trial. Successful and effective implementation of this QI tool could support the detection of patients at risk of undiagnosed cancer in primary care and assist in preventing unnecessary delays.

Evolution delayed decision game based on carbon emission and capacity sharing in the Chinese market

Based on the carbon emission policy and low-carbon capacity sharing, this paper studies the optimal product pricing and capacity matching strategies of competition and cooperation between two companies in a duopoly market. And the optimal strategies with or without capacity sharing are discussed. In addition, a differential game model based on carbon emission constraints, low-carbon capacity sharing, and delayed decision-making is established. We also study the evolution of duopoly enterprises from the initial state to the equilibrium state. Besides, the influence of delayed decision variables, price adjustment speed and decision weights on the stability of the game system is analyzed. The results show that the government can effectively intervene and guide the enterprises’ low-carbon production strategy through carbon emission restriction policy. Low-carbon capacity sharing is beneficial to both enterprises, and the demand side benefits more than the supply side. We discuss the impact of stable and unstable systems on enterprises’ decisions. When the system is stable, enterprises can converge from different initial game states to equilibrium states. The adoption of a delay strategy will not affect the tendency of convergence to the equilibrium. Furthermore, the system using the variable feedback control method is of higher stability.

A hybrid INDI control for ensuring flying qualities in failures of Xcg measurement subsystem

Modern version of fighter aircraft has a wide range of longitudinal center-of-gravity (Xcg) travel due to wide-range fuel tanks layout, various weapons, many payload stations, and so on. The wide Xcg travel degrades flying qualities of a closed-loop control system; moreover, a catastrophic accident can be caused by loss of stability due to the wide Xcg travel in severe cases. For this reason, the inner-loop control law generally employs additional feedback variables such as weight and Xcg position to guarantee the flying qualities and satisfy stability requirements. Nevertheless, this design approach can seriously deteriorate the flight safety and stability of the aircraft in the event of fuel mismanagement and Xcg measurement subsystem failures. Therefore, additional design technique should be considered to ensure the flight safety in response to the situation of the failure conditions. This paper proposes two types of a hybrid Incremental Nonlinear Dynamic Inversion control to guarantee the minimum flight safety for return to base in case of fuel mismanagement and Xcg measurement subsystem failures. The frequency-domain linear analysis and time-domain simulations were performed based on a supersonic trainer mathematical model to evaluate the performances of the proposed control methods. The evaluation results confirm that the proposed control method satisfies the level of the required flying qualities and ensure flight safety even in the event of the subsystem failures for the Xcg measurement.

Inter-Trial Formant Variability in Speech Production Is Actively Controlled but Does Not Affect Subsequent Adaptation to a Predictable Formant Perturbation.

Despite ample evidence that speech production is associated with extensive trial-to-trial variability, it remains unclear whether this variability represents merely unwanted system noise or an actively regulated mechanism that is fundamental for maintaining and adapting accurate speech movements. Recent work on upper limb movements suggest that inter-trial variability may be not only actively regulated based on sensory feedback, but also provide a type of workspace exploration that facilitates sensorimotor learning. We therefore investigated whether experimentally reducing or magnifying inter-trial formant variability in the real-time auditory feedback during speech production (a) leads to adjustments in formant production variability that compensate for the manipulation, (b) changes the temporal structure of formant adjustments across productions, and (c) enhances learning in a subsequent adaptation task in which a predictable formant-shift perturbation is applied to the feedback signal. Results show that subjects gradually increased formant variability in their productions when hearing auditory feedback with reduced variability, but subsequent formant-shift adaptation was not affected by either reducing or magnifying the perceived variability. Thus, findings provide evidence for speakers’ active control of inter-trial formant variability based on auditory feedback from previous trials, but–at least for the current short-term experimental manipulation of feedback variability–not for a role of this variability regulation mechanism in subsequent auditory-motor learning.

Stability Simulation of 150 kV Malang Power Grid

This research describes the oscillation control based on a power system that takes the place of the traditional automatic voltage regulators for excitation control in addition to a multimachine power system. The design is built on equilibrium and a potent adaptive critic technique called decreasing time oscillation for each generator. The generators' local measurements serve as the sole basis for the feedback variables. For enhancing the dynamic performance and stability of the power grid under significant shocks that affected oscillation power stations, simulations on multi-machine power systems were shown to be effective.