Closed-loop Control Algorithm Research Articles

Automated oxygen delivery for preterm infants with respiratory dysfunction.

Many preterm infants require respiratory support to maintain an optimal level of oxygenation, as oxygen levels both below and above the optimal range are associated with adverse outcomes. Optimal titration of oxygen therapy for these infants presents a major challenge, especially in neonatal intensive care units (NICUs) with suboptimal staffing. Devices that offer automated oxygen delivery during respiratory support of neonates have been developed since the 1970s, and individual trials have evaluated their effectiveness. To assess the benefits and harms of automated oxygen delivery systems, embedded within a ventilator or oxygen delivery device, for preterm infants with respiratory dysfunction who require respiratory support or supplemental oxygen therapy. We searched CENTRAL, MEDLINE, CINAHL, and clinical trials databases without language or publication date restrictions on 23 January 2023. We also checked the reference lists of retrieved articles for other potentially eligible trials. We included randomised controlled trials and randomised cross-over trials that compared automated oxygen delivery versus manual oxygen delivery, or that compared different automated oxygen delivery systems head-to-head, in preterm infants (born before 37 weeks' gestation). We used standard Cochrane methods. Our main outcomes were time (%) in desired oxygen saturation (SpO2) range, all-cause in-hospital mortality by 36 weeks' postmenstrual age, severe retinopathy of prematurity (ROP), and neurodevelopmental outcomes at approximately two years' corrected age. We expressed our results using mean difference (MD), standardised mean difference (SMD), and risk ratio (RR) with 95% confidence intervals (CIs). We used GRADE to assess the certainty of evidence. We included 18 studies (27 reports, 457 infants), of which 13 (339 infants) contributed data to meta-analyses. We identified 13 ongoing studies. We evaluated three comparisons: automated oxygen delivery versus routine manual oxygen delivery (16 studies), automated oxygen delivery versus enhanced manual oxygen delivery with increased staffing (three studies), and one automated system versus another (two studies). Most studies were at low risk of bias for blinding of personnel and outcome assessment, incomplete outcome data, and selective outcome reporting; and half of studies were at low risk of bias for random sequence generation and allocation concealment. However, most were at high risk of bias in an important domain specific to cross-over trials, as only two of 16 cross-over trials provided separate outcome data for each period of the intervention (before and after cross-over). Automated oxygen delivery versus routine manual oxygen delivery Automated delivery compared with routine manual oxygen delivery probably increases time (%) in the desired SpO2 range (MD 13.54%, 95% CI 11.69 to 15.39; I2 = 80%; 11 studies, 284 infants; moderate-certainty evidence). No studies assessed in-hospital mortality. Automated oxygen delivery compared to routine manual oxygen delivery may have little or no effect on risk of severe ROP (RR 0.24, 95% CI 0.03 to 1.94; 1 study, 39 infants; low-certainty evidence). No studies assessed neurodevelopmental outcomes. Automated oxygen delivery versus enhanced manual oxygen delivery There may be no clear difference in time (%) in the desired SpO2 range between infants who receive automated oxygen delivery and infants who receive manual oxygen delivery (MD 7.28%, 95% CI -1.63 to 16.19; I2 = 0%; 2 studies, 19 infants; low-certainty evidence). No studies assessed in-hospital mortality, severe ROP, or neurodevelopmental outcomes. Revised closed-loop automatic control algorithm (CLACfast) versus original closed-loop automatic control algorithm (CLACslow) CLACfast allowed up to 120 automated adjustments per hour, whereas CLACslow allowed up to 20 automated adjustments per hour. CLACfast may result in little or no difference in time (%) in the desired SpO2 range compared to CLACslow (MD 3.00%, 95% CI -3.99 to 9.99; 1 study, 19 infants; low-certainty evidence). No studies assessed in-hospital mortality, severe ROP, or neurodevelopmental outcomes. OxyGenie compared to CLiO2 Data from a single small study were presented as medians and interquartile ranges and were not suitable for meta-analysis. Automated oxygen delivery compared to routine manual oxygen delivery probably increases time in desired SpO2 ranges in preterm infants on respiratory support. However, it is unclear whether this translates into important clinical benefits. The evidence on clinical outcomes such as severe retinopathy of prematurity are of low certainty, with little or no differences between groups. There is insufficient evidence to reach any firm conclusions on the effectiveness of automated oxygen delivery compared to enhanced manual oxygen delivery or CLACfast compared to CLACslow. Future studies should include important short- and long-term clinical outcomes such as mortality, severe ROP, bronchopulmonary dysplasia/chronic lung disease, intraventricular haemorrhage, periventricular leukomalacia, patent ductus arteriosus, necrotising enterocolitis, and long-term neurodevelopmental outcomes. The ideal study design for this evaluation is a parallel-group randomised controlled trial. Studies should clearly describe staffing levels, especially in the manual arm, to enable an assessment of reproducibility according to resources in various settings. The data of the 13 ongoing studies, when made available, may change our conclusions, including the implications for practice and research.

Three link flexible arm robust regulation via proportional retarded control scheme

In this paper, a delayed distributed proportional control is developed for a class of multiple-input-multiple-output systems in order to reduce the effects of external disturbances and uncertain dynamics. The system under consideration is a three degrees-of-freedom planar robot, consisting of an active joint driving the first link and passive flexible joints for the second and third links. The control challenge for this system is to drive the flexible arm around the desired setpoint or trajectory by controlling the first link. Actually, by using a specific Lyapunov-Krasovskii storage functional associated with a constrained optimization problem, the robustness of the proposed proportional retarded control action is achieved. This analysis, together with the attractive ellipsoid concept allows to conclude with Ultimately-Uniformly-Bounded stability. The closed-loop control algorithm is tested in numerical simulation and a comparative study with some existing recent control schemes based on the performance error is presented.

Coil Position Control Technology in Magnetic Coupled Wireless Power Transmission

This article mainly studies the issue of power and efficiency fluctuations at the receiving end caused by changes in the relative positions of the transmitting coil and the receiving coil in a magnetic coupled radio energy transmission system. A circuit model was built to analyze the logical relationship of energy transmission in a wireless energy transmission system, and the optimal transmission position of the two-coil system was calculated. Simulation analysis and experimental measurements were conducted to obtain the transmission power of the coil at different distances. Based on the microcontroller, a closed-loop automatic control algorithm is designed for the laser rangefinder and the stepping motor. When the position of the receiving coil changes, the transmitting coil can move with the position of the receiving coil so that the system can quickly stabilize at the optimal power transmission point. The method used in this article can achieve stable transmission power of over 7 W when the receiving coil moves 0-100 cm along the axis.

Design of a Redundant 6-DOF Parallel Platform for Mirror Precision Pose Adjustment

The pose control of 6-DOF parallel mechanism depends on the measurement accuracy of the position of the active driving strut, which affects the pose control accuracy of 6-DOF parallel mechanism. In order to overcome the influence of heavy load large impact force on the measurement accuracy of the active drive strut, a redundant 6-DOF parallel mechanism that separates the measurement struts from the active drive struts was proposed. The fixed platform and the moving platform are connected by six identical active drive struts and six redundant measurement struts. The active driving strut is an active motion unit used to achieve various pose movements of the parallel mechanism, and the follower redundant measurement strut is a precision measurement unit, and does not constrain any DOF of the platform. Only the follower accurately measures the distance between the upper and lower hinge points of the redundant hinges. The accurate position and pose of the 6-DOF parallel mechanism are obtained by using the forward kinematics solution. The controller is used to implement the pose closed-loop control algorithm to achieve precise pose control. The design of this redundant 6-DOF parallel mechanism improves the movement accuracy of the parallel mechanism under heavy load. It can be applied to the precision adjustment of the primary mirror or secondary mirror under heavy load in large aperture optics, and has strong engineering application value.

An Adaptive Model Predictive Controller to Address the Biovariability in Blood Clotting Response During Therapy With Warfarin.

Effective dosing of anticoagulants aims to prevent blood clot formation while avoiding hemorrhages. This complex task is challenged by several disturbing factors and drug-effect uncertainties, requesting frequent monitoring and adjustment. Biovariability in drug absorption and action further complicates titration and calls for individualized strategies. In this paper, we propose an adaptive closed-loop control algorithm to assist in warfarin therapy management. The controller was designed and tested in silico using an established pharmacometrics model of warfarin, which accounts for inter-subject variability. The control algorithm is an adaptive Model Predictive Control (a-MPC) that leverages a simplified patient model, whose parameters are updated with a Bayesian strategy. Performance was quantitatively evaluated in simulations performed on a population of virtual subjects against an algorithm reproducing medical guidelines (MG) and an MPC controller available in the literature (l-MPC). The proposed a-MPC significantly (p 0.05) lowers rising time (2.8 vs. 4.4 and 11.2 days) and time out of range (3.3 vs. 7.2 and 12.9 days) with respect to both MG and l-MPC, respectively. Adaptivity grants a significantly (p 0.05) lower number of subjects reaching unsafe INR values compared to when this feature is not present (8.9% vs.15% of subjects presenting an overshoot outside the target range and 0.08% vs. 0.28% of subjects reaching dangerous INR values). The a-MPC algorithm improve warfarin therapy compared to the benchmark therapies. This in-silico validation proves effectiveness of the a-MPC algorithm for anticoagulant administration, paving the way for clinical testing.

An adaptive robust path-tracking control algorithm of multi-articulated and redundantly actuated virtual track train

Multi-articulated and redundantly actuated virtual track trains (VTTs) are inevitably exposed to unknown exogenous disturbances and various operating conditions. To address the complex over-actuated tracking-control problem, this study proposes a decoupling control scheme for an all-wheel independent drive and all-wheel active steering VTT composed of multiple modules, wherein the adaptive robust path-tracking and longitudinal speed control algorithms of the VTT are decoupled. An appropriate control-oriented nonlinear dynamic model for VTT path-tracking control is formulated using Lagrange’s equations. To compensate for the model uncertainties and environmental disturbances without priors and parameter estimations, a robust control algorithm using radial basis function neural network and sliding mode is proposed. The asymptotic stability of the algorithm is proved, and its adaptation law is derived using the Lyapunov theory. Moreover, a novel traction/braking control algorithm based on the wheel speed distribution model and double closed-loop control algorithm is suggested. Using a multi-body dynamic model of the VTT with seven modules, simulations are performed to evaluate the effectiveness and superiority of the proposed path-tracking algorithm. The obtained results indicate that the proposed algorithm could realise the expectable performance of the VTT path tracking and longitudinal speed control. Moreover, the proposed control algorithm has good scalability for multi-articulated and redundantly actuated VTT.

(Invited) smart Wearable Electronics for Chronic Disease Management

60% of Americans live with at least one chronic disease. These diseases and associated comorbidities are now the leading causes of death in the United States. Effective management of complex chronic diseases requires body-wide, long-term, accurate, and continuous monitoring of multiple physiological signals from wearable devices to precisely determine the pathological state. These wearable physiological signal monitoring can dramatically reduce the demand of physician visiting and increase patients’ engagement and treatment adherence rate. Although wearable bioelectronic devices have shown huge potential in chronic disease management, existing technology still mostly relies on rigid chip components, where the interface between chips and skin/tissue has been a bottleneck that limits the system performance (noise, robustness etc). To address these challenges, my research has been involved in the exploration of rational system design concepts, material and device fabrication innovation, and tailored algorithms to enable smart wearable electronics that targets next-generation chronic disease management.Here I would like to discuss two of my developed technology platforms to elaborate the concept of smart wearables. First, I will describe a body area sensor network technology platform. In the system design concept side, this technology utilizes a novel wireless hybridization strategy and an unconventional detuned RFID working regime that provide an ideal skin interface. In the material/device side, this system integrates several skin-conforming polymer-based soft devices (ring oscillators, RF diodes, antennas, transistors etc.) as an integrated soft multimode sensing sticker. (1,2) Next, I will describe a wireless closed-loop smart bandage that can accelerate and monitor the wound healing process. (3) Such smart bandage also integrates new design concepts (wireless, battery-free design that combines both sensing and stimulation), novel materials (low-impedance, high-toughness, and tunable adhesion hydrogel as skin interface) and closed-loop control algorithms. Overall, the developed technology platform could assess multiple health outcomes and treatment responses to various chronic diseases. Ultimately, this technology will help to reduce chronic disease burden, lower medical costs, and provide a better quality of life for patients.

An improved MITC3 element for vibration response analysis of piezoelectric functionally graded porous plates

The main goal of this paper is to improve the mixed interpolation of tensorial components triangular (MITC3) by using the edge-based smoothed finite element method (ES-FEM), so-called ES-MITC3, for analyzing the vibration of piezoelectric functionally graded porous (p-FGP) plates subjected to dynamic loading. The material properties of the FGP core vary through thickness with uneven porosity distribution. Besides, the linear relationship between the electric potential and the thickness of the piezoelectric sublayer is taken into account. A closed-loop control algorithm is employed to actively control the vibration of p-FGP plates, through feedback from displacement and velocity. The performance of the proposed method is verified through comparative examples. Finally, the authors hope that the present method can be effectively applied to many smart material models in a multiphysics environment and contribute to understanding texture control by piezoelectric materials through numerical results.

A Population-Informed Particle Filter for Robust Physiological Monitoring Using Low-Information Time-Series Measurements.

To present the population-informed particle filter (PIPF), a novel filtering approach that incorporates past experiences with patients into the filtering process to provide reliable beliefs about a new patient's physiological state. To derive the PIPF, we formulate the filtering problem as recursive inference on a probabilistic graphical model, which includes representations for the pertinent physiological dynamics and the hierarchical relationship between past and present patient characteristics. Then, we provide an algorithmic solution to the filtering problem using Sequential Monte-Carlo techniques. To demonstrate the merits of the PIPF approach, we apply it to a case study of physiological monitoring for hemodynamic management. The PIPF approach could provide reliable beliefs about the likely values and uncertainties associated with a patient's unmeasured physiological variables (e.g., hematocrit and cardiac output), characteristics (e.g., tendency for atypical behavior), and events (e.g., hemorrhage) given low-information measurements. The PIPF shows promise in the presented case study, and may have applications to a wider range of real-time monitoring problems with limited measurements. Forming reliable beliefs about a patient's physiological state is an essential aspect of algorithmic decision-making in medical care settings. Hence, the PIPF may serve as a solid basis for designing interpretable and context-aware physiological monitoring, medical decision-support, and closed-loop control algorithms.

Combined hydrodynamic and control analysis on optimal kinematic parameters for bio-inspired autonomous underwater vehicle manoeuvring

To investigate the manoeuvring performance of a body-caudal fin robot fish, a numerical framework combining computational fluid dynamics and multi-body dynamics with a closed-loop control algorithm was established in this study. Within this framework, we modelled a body-caudal fin swimmer as a multi-body system with the shape of a NACA0012 hydrofoil. The manoeuvring performance was investigated by using different curvature magnitudes and distributions along the centre line (the curvature is defined by means of a curvature envelop function as part of the general body undulation equation). To characterize the turning performance, a new parameter named cost of manoeuvring (CoM) is proposed. This parameter provides a combined assessment of the turning radius, linear and angular velocity components, and power. It is found that when the body curvature is introduced, the swimmer switches from straight-line swimming to quasi-steady turning at a constant speed. Further investigations were conducted to study contributions of head and tail deformations on the turning performance by comparing predominantly head and tail curved envelopes. Results reveal that a tail-dominated envelope improves performance, whereas a head-dominated envelope has a negative effect.

Integration and preliminary evaluation of a robotic cotton harvester prototype

Cotton is conventionally harvested with large and costly harvesters once at the end of the growing season. Fiber in the early-opened bolls is left on the plants till the end of the season to be harvested, resulting in its exposure to weather and thus degraded quality. Furthermore, heavy cotton harvesters can compact the soil and adversely affect soil health and crop yield. These issues can potentially be addressed by using small robotic cotton harvesters that can harvest multiple times during the season, picking seed cotton soon after the bolls open. Robotic cotton harvesters are not currently available. This article presents the system integration and performance evaluation of a new robotic cotton harvester prototype consisting of a 3-DOF (degrees of freedom) linear robotic arm with a custom three-finger end-effector, integrated with a deep-learning based perception module to enable fast and automatic harvesting of cotton. The perception system utilized a stereovision camera and an onboard computer with a trained YOLOv4-tiny algorithm for detecting and locating cotton bolls within the plant. Three different control algorithms were examined to control manipulation of the arm and run the end-effector throughout the harvesting process. Performance of the harvester was evaluated in terms of picking ratio – picked seed cotton over available seed cotton in the image – and cycle time through laboratory tests using real cotton plants. Results showed that a closed-loop control algorithm using continuous feedback from cotton boll images during picking was the most efficient, successfully harvesting 72% of the seed cotton with an average cycle time of 8.8 s.

Novel closed-loop dual control algorithm for solar trackers of parabolic trough collector systems

Parabolic trough systems require accurate, reliable, and robust solar trackers to achieve their maximum thermal efficiency. This paper presents a dual closed-loop control strategy for single-axis solar trackers of parabolic trough systems. This strategy consists of the use of a dual control feedback through the integration of a typical photodiode-based solar sensors, to perform the coarse control, and a proposed shadow-based visual device that performs the fine position adjustment. A comparative analysis between a simple closed-loop control, typically used in parabolic trough systems, and the proposed control algorithm was conducted. Experimental tests were carried out for several days under different weather conditions. The experimental results showed that the mean solar tracking error obtained with the simple control was 0.97°, while the error of the proposed dual control was 0.21°; i.e., the error decreased by 78%, demonstrating greater stability and robustness of solar tracking. The proposed strategy proved to be a technically and economically feasible option to increase accuracy, reliability, and robustness in single-axis solar tracking systems of parabolic trough systems.

Vibration and dynamic control of piezoelectric functionally graded porous plates in the thermal environment using FEM and Shi’s TSDT

This paper proposes a new finite element formulation based on Shi’s third-order shear deformation theory (TSDT) for controlling the vibration of piezoelectric functionally graded porous (PFGP) plates integrated with piezoelectric sensors and actuators under dynamic loading in the high temperature environment. The properties of the PFGP core vary through the plate’s thickness according to the power-law index k and porosity factor Ω, while the electric potential is a linear function via the piezoelectric sublayer thickness. To actively control the vibration of PFGP plates, a closed-loop control algorithm based on displacement and velocity feedback is applied. The motion equation of PFGP plate under mechanical and thermal load is established based on based on Galerkin weak formulation. The proposed method is evaluated through several numerical examples to demonstrate its effectiveness. Furthermore, the active vibration control of FPGP plates is detail presented.

Modulation of motor responses and neural activities with transcranial ultrasound stimulation based on closed-loop control

Closed-loop transcranial ultrasound stimulation technology is based on real-time feedback signals, and has the potential for precise regulation of neural activity. In this paper, firstly the local field potential (LFP) and electromyogram (EMG) signals of mice under different intensities of ultrasound stimulation were recorded, then the mathematical model of ultrasound intensity and mouse LFP peak/EMG mean was established offline based on the data, and the closed-loop control system of LFP peak and EMG mean based on PID neural network control algorithm was simulated and built to realize closed-loop control of LFP peak and EMG mean of mice. In addition, using the generalized minimum variance control algorithm, the closed-loop control of theta oscillation power was realized. There was no significant difference between the LFP peak, EMG mean and theta power under closed-loop ultrasound control and the given value, indicating a significant control effect on the LFP peak, EMG mean and theta power of mice. Transcranial ultrasound stimulation based on closed-loop control algorithms provides a direct tool for precise modulation of electrophysiological signals in mice.

Effect of Wavefront Distortion on the Performance of Coherent Detection Systems: Theoretical Analysis and Experimental Research

Atmospheric turbulence causes signal beam wavefront distortion at the receiving end of a coherent detection system, which decreases the system mixing efficiency. Based on the coherent detection theory, this study establishes a mathematical model of wavefront distortion with mixing efficiency and mixing gain. It also analyzes the improvement limits of wavefront correction on mixing efficiency and mixing gain under different atmospheric turbulence intensities and experimentally measures them. Simulation results show that the mixing efficiency can be improved to 51%, 55%, and 60% after correcting for tilt, defocus, and astigmatism terms, respectively, when turbulence intensity D/r0 is 2. The mixing gain with homodyne detection is 3 dB higher than heterodyne detection. Meanwhile, the wavefront correction orders required for optimal mixing efficiency are higher than the heterodyne correction order. In the experiment, Haso4 NIR + DM 40 was used, and the turbulence intensity D/r0 was 2. After the closed-loop control algorithm corrects the tilt, defocus, and astigmatism terms, the indoor experimental results showed that the mixing efficiency is improved to 36%, 47%, and 62%, respectively. The outdoor experimental results showed that the mixing efficiency improved to 36%, 51%, and 68%, respectively.

Wearable, Sensing-Controlled, Ultrasound-Based Microneedle Smart System for Diabetes Management.

An intelligent closed-loop system that senses glucose and automatically delivers insulin can provide enhanced glycemic control for diabetes management. Here, we report for the first time on the development of a wearable, sensing-controlled, ultrasound-based closed-loop microneedle smart system for diabetes management. Polylactic acid (PLA) hollow microneedles were fabricated by soft lithography that can maintain excellent mechanical strength and stability in biofluids, followed by the deposition of sensing electrodes on the outer layer. An ultrasonic insulin pump was constructed by integrating a lead zirconate titanate piezoelectric (PZT) ring and a biocompatible stainless-steel sheet with hundreds of tapered holes on top of the inner layer of the microneedles. Both the sensor and the pump were powered and controlled by a printed circuit board (PCB). When the sensing device detects interstitial glucose levels above normal, the closed-loop control algorithm triggers the ultrasonic pump to deliver insulin into the interstitial fluid through the microneedle hollow channels of the PLA microneedles. The ultrasound from the pump can cause the vaporization of insulin in the subcutaneous tissue fluid, accelerate the diffusion rate, and improve the efficiency of insulin treatment and utilization. The system has successfully demonstrated effective control of glucose levels in diabetic rats. The glucose sensor showed a high sensitivity of 0.212 μA/mM at 0-28 mM with a detection limit of 14 μM, and the mean absolute relative difference (MARD) was 9.96% with an average error of 1.6 mM. The flow rate of the ultrasonic pump was 120 μL/min, and the glucose-lowering rate was 4 mM/h. This work may open a new paradigm for the development of intelligent systems for diabetes management, as well as a wide range of practical applications in diabetes patients.

Control Analysis of Vehicle Steering System based on Closed-Loop Control Algorithm

When a four-wheel vehicle turns and the steering centre of the front and rear wheels is one point, it is regarded as the theoretical optimal steering of the vehicle and the goal of optimal control. Aiming at the commonly used multi-link steering system, the system control was analysed, according to the structural characteristics and angle relationship. Based on the closed-loop control algorithm, the optimal control of the steering system was designed and analysed, according to the steering control quantity obtained by the target path and parameter feedback. At the same time, the state variables and prediction parameters of the system were analysed. Based on the actual vehicle and steering optimal control system, the changes of various parameters of vehicle operation under no-load condition and turning at 30 km/h were analysed and compared with the theoretical optimal value to verify the effectiveness of the control system. The results show that: the state variables of the control system are predicted by discrete analysis and half step integration, and the accuracy is high. In the steady state turning condition, with the lifting of the vehicle, the radius of the steering track gradually increases, and the vehicle shows obvious understeer characteristics. Under the two working conditions, the characteristic curves obtained by the steering control system are highly consistent with the theoretical values, and the peak error of the two is controlled within 5%, indicating the reliability of the optimal control algorithm, which provides a reference for such design optimization.

Design of Double Closed Loop Control System for DC Motor Based on TX8C1010 Single Chip

In order to improve the operational strength and control precision of the DC motor, a double closed-loop control system based on TAIXIN TX8C1010 MCU is proposed. The single chip is based on a high-speed 8051 core, which is applied to home appliances and can realize the double closed-loop motor control algorithm. The given speed value provided by the potentiometer is compared with the real-time speed value and inputs the error to the speed loop function, which is based on the incremental PID algorithm, to calculate the reference current value. Then it is compared with the real-time current value and inputs the error into the current loop. The PWM signal duty cycle is determined by the output value of the current loop to adjust and stabilize the motor speed. The drive circuit outputs the PWM signal in the inverse amplification way to control the operation of the DC motor, and finally tests the function on the MAGTROL M-TEST7 motor test platform. The test results show that the control system has fast response speed, strong load capacity, good robustness and safety. Hence, TAIXIN TX8C1010 single-chip machine is feasible in the DC motor control. It can be improved to strengthen its load characteristics according to the parameters and applied to a variety of power DC motor control.

Soft Robotic Glove with Sensing and Force Feedback for Rehabilitation in Virtual Reality.

Many diseases, such as stroke, arthritis, and spinal cord injury, can cause severe hand impairment. Treatment options for these patients are limited by expensive hand rehabilitation devices and dull treatment procedures. In this study, we present an inexpensive soft robotic glove for hand rehabilitation in virtual reality (VR). Fifteen inertial measurement units are placed on the glove for finger motion tracking, and a motor-tendon actuation system is mounted onto the arm and exerts forces on fingertips via finger-anchoring points, providing force feedback to fingers so that the users can feel the force of a virtual object. A static threshold correction and complementary filter are used to calculate the finger attitude angles, hence computing the postures of five fingers simultaneously. Both static and dynamic tests are performed to validate the accuracy of the finger-motion-tracking algorithm. A field-oriented-control-based angular closed-loop torque control algorithm is adopted to control the force applied to the fingers. It is found that each motor can provide a maximum force of 3.14 N within the tested current limit. Finally, we present an application of the haptic glove in a Unity-based VR interface to provide the operator with haptic feedback while squeezing a soft virtual ball.

Stabilizing a strongly nonlinear structure through shaker dynamics in fixed frequency voltage control tests

Bifurcations are commonly encountered during force controlled swept and stepped sine testing of nonlinear structures, which generally leads to the so-called jump-down or jump-up phenomena between stable solutions. There are various experimental closed-loop control algorithms, such as control-based continuation and phase-locked loop, to stabilize dynamical systems through these bifurcations, but they generally rely on specialized control algorithms that are not readily available with many commercial data acquisition software packages. A recent method was developed to experimentally apply sequential continuation using the shaker voltage that can be readily deployed using commercially available software. By utilizing the stabilizing effects of electrodynamic shakers and the force dropout phenomena in fixed frequency voltage control sine tests, this approach has been demonstrated to stabilize the unstable branch of a nonlinear system with three branches, allowing for three multivalued solutions to be identified within a specific frequency bandwidth near resonance. Recent testing on a strongly nonlinear system with vibro-impact nonlinearity has revealed jumping behavior when performing sequential continuation along the voltage parameter, like the jump phenomena seen during more traditional force controlled swept and stepped sine testing. This paper investigates the stabilizing effects of an electrodynamic shaker on strongly nonlinear structures in fixed frequency voltage control tests using both numerical and experimental methods. The harmonic balance method is applied to the coupled shaker-structure system with an electromechanical model to simulate the fixed voltage control tests and predict the stabilization for different parameters of the model. The simulated results are leveraged to inform the design of a set of experiments to demonstrate the stabilization characteristics on a fixture-pylon assembly with a vibro-impact nonlinearity. Through numerical simulation and experimental testing on two different strongly nonlinear systems, the various parameters that influence the stability of the coupled shaker-structure are revealed to better understand the performance of fixed frequency voltage control tests.