Closed-loop Feedback Control Research Articles

A method to improve the modulation depth servo accuracy of an integrated fiber-optic gyroscope using the Bouc-Wen model

The development of integrated fiber-optic gyroscopes using piezoelectric modulation (PEM) represents a significant advance in the field of fiber-optic gyroscopes. However, the hysteretic creep nonlinearity of Piezoe-lectric Transducer (PZT) affects the modulation depth monitoring and leads to a drift of its resonant frequency. The accuracy of the PEM's closed-loop feedback signal determines the open-loop gyroscope's accuracy. However, the hysteresis deteriorates the controller phase and the gain margin, inducing the fluctuation of the amplitude of each harmonic wave, which undoubtedly increases the difficulty of the closed-loop feedback control of the modulator. This paper proposes a method to quantify the high-frequency hysteresis nonlinearity of PZT, combining the advantages of feedforward compensation and feedback closed-loop. Feedforward compensation is used to reduce the hysteresis nonlinearity of PEM, reduce the interference of the nonlinear phase shift to zero drift, and increase the control accuracy of feedback control to PEM under temperature disturbance.

Nanoindentation plasticity and loading rate sensitivity of laser additive manufactured functionally graded 316L and 410L stainless steels

The present work is the first to show the effect of processing cooling rate on phase structure and the resulting nano-scale deformation mechanisms in functionally graded stainless steels produced by directed energy deposition. To this end, fabrication by laser additive manufacturing involved implementing a closed-loop feedback control approach to monitor and control the peak temperature of the molten pool and the corresponding cooling rate. Single-track wall structures were produced from 316-L austenitic and 410-L martensitic stainless steels deposited using open-loop conditions with varying processing parameters (laser power and beam scanning speed) to produce graded microstructures. These were then compared to uniformly deposited layers where a constant cooling rate was maintained to generate homogenous microstructures using these two alloys, containing well-aligned columnar austenitic grains and random martensitic packets. Microstructural aspects (grains and crystallographic texture) across different layers (bottom, middle, and top) of the consolidated stainless steel walls (austenitic and martensitic) were compared under various processing conditions (without and with closed-loop or feedback control) and characterized using electron backscattering diffraction analysis. The nano-scale plastic deformation of these austenitic and martensitic stainless steel structures were assessed using nanoindentation testing over a range loading rates from 1 to 50 mN/s. The indentation response using varying strain rates was investigated based on the plastic flow indenting transition behavior at a high loading rate in order to correlate their dependence on microstructural features (predominantly for the martensitic phase). According to the rate sensitivity analyses, the gradient in grain structure (size and morphology) in the case of additively manufactured austenitic microstructure was not sensitive to loading rate, while the martensitic grains had a high local loading rate sensitivity.

Doubling the Space-Time Yield of a Pilot Biogas Reactor with Swine Manure and Cereal Residues by a Closed Loop Feedback Control Based on an Automated Fuzzy Logic Control System

The anaerobic digestion of swine manure was performed for more than 2 years in a biogas pilot plant with cereal residues as a mono-input, either by a simple intermittent substrate feeding or by feeding with an automated “autopilot” system under the direction of a Fuzzy logic control (FLC) system, working with a closed-loop feedback control. The pilot plant of the University of Applied Sciences in Nordhausen consisted of a 2.5 m3 dosage tank, a 2.5 m3 digestate tank, and a 1 m3 biogas reactor. Only three control parameters were used for FLC: pH, methane %, and the specific gas production rate (GPR) related to the organic loading rate (OLR), that is GPR/OLR m3 biogas/(kgVS d), vs = volatile solids. The specific GPR was referred to the OLR of the last feeding every 8 h in terms of kgVS/(m3 d). In test period I without an FLC system, a safe process with just an OLR of 4 kgVS/(m3 d) was reached, followed by an overloading and reactor disturbance at ≤6.3 kgVS/(m3 d) as indicated by acidification with volatile fatty acids up to 25,000 mg/L. However, test period II (585 trial days) with an integrated FLC system allowed a safe OLR up to 11 kgVS/(m3 d). Apparently, the microbes themselves directed the speed of substrate feeding by the dynamics of their substrate turnover and by the closed loop feedback control, while the three FLC parameters prevented acidification. Therefore, the application of FLC enabled a doubling of the throughput for a biogas reactor in the same time with a ‘turbo speed’. The concomitant hydraulic residence time (HRT) of only 10 days reduced the stirring and heating costs. The usage of an FLC system should open the door for networked biogas production to enable flexible biogas production on demand.

An autonomous microchip for real-time, label-free immune cell analysis

Characterization of cell populations and identification of distinct subtypes based on surface markers are needed in a variety of applications from basic research and clinical assays to cell manufacturing. Conventional immunophenotyping techniques such as flow cytometry or fluorescence microscopy require immunolabeling of cells, expensive and complex instrumentation, skilled operators, and are therefore incompatible with field deployment and automated cell manufacturing systems. In this work, we introduce an autonomous microchip that can electronically quantify the immunophenotypical composition of a cell suspension. Our microchip identifies different cell subtypes by capturing each in different microfluidic chambers functionalized against the markers of the target populations. All on-chip activity is electronically monitored by an integrated sensor network, which informs an algorithm determining subpopulation fractions from chip-wide immunocapture statistics in real time. Moreover, optimal operational conditions within the chip are enforced through a closed-loop feedback control on the sensor data and the cell flow speed, and hence, the antibody-antigen interaction time is maintained within its optimal range for selective immunocapture. We apply our microchip to analyze a mixture of unlabeled CD4+ and CD8+ T cell sub-populations and then validated the results against flow cytometry measurements. The demonstrated capability to quantitatively analyze immune cells with no labels has the potential to enable not only autonomous biochip-based immunoassays for remote testing but also cell manufacturing bioreactors with built-in, adaptive quality control.

A review: Machine learning for strain sensor-integrated soft robots

Compliant and soft sensors that detect machinal deformations become prevalent in emerging soft robots for closed-loop feedback control. In contrast to conventional sensing applications, the stretchy body of the soft robot enables programmable actuating behaviors and automated manipulations across a wide strain range, which poses high requirements for the integrated sensors of customized sensor characteristics, high-throughput data processing, and timely decision-making. As various soft robotic sensors (strain, pressure, shear, etc.) meet similar challenges, in this perspective, we choose strain sensor as a representative example and summarize the latest advancement of strain sensor-integrated soft robotic design driven by machine learning techniques, including sensor materials optimization, sensor signal analyses, and in-sensor computing. These machine learning implementations greatly accelerate robot automation, reduce resource consumption, and expand the working scenarios of soft robots. We also discuss the prospects of fusing machine learning and soft sensing technology for creating next-generation intelligent soft robots.

Deep reinforcement learning achieves multifunctional morphing airfoil control

Smooth camber morphing aircraft offer increased control authority and improved aerodynamic efficiency. Smart material actuators have become a popular driving force for shape changes, capable of adhering to weight and size constraints and allowing for simplicity in mechanical design. As a step towards creating uncrewed aerial vehicles (UAVs) capable of autonomously responding to flow conditions, this work examines a multifunctional morphing airfoil’s ability to follow commands in various flows. We integrated an airfoil with a morphing trailing edge consisting of an antagonistic pair of macro fiber composites (MFCs), serving as both skin and actuator, and internal piezoelectric flex sensors to form a closed loop composite system. Closed loop feedback control is necessary to accurately follow deflection commands due to the hysteretic behavior of MFCs. Here we used a deep reinforcement learning algorithm, Proximal Policy Optimization, to control the morphing airfoil. Two neural controllers were trained in a simulation developed through time series modeling on long short-term memory recurrent neural networks. The learned controllers were then tested on the composite wing using two state inference methods in still air and in a wind tunnel at various flow speeds. We compared the performance of our neural controllers to one using traditional position-derivative feedback control methods. Our experimental results validate that the autonomous neural controllers were faster and more accurate than traditional methods. This research shows that deep learning methods can overcome common obstacles for achieving sufficient modeling and control when implementing smart composite actuators in an autonomous aerospace environment.

In-situ monitoring of powder bed fusion of polymers using laser profilometry

Process monitoring allows for unique opportunities to capture information at intermediate layers during fabrication for part qualification, but also to improve process robustness by identifying issues before yield or quality is reduced. An industrial-grade laser profilometer has been integrated for the first time in a commercial polymer laser sintering machine and used to monitor powder bed quality and potentially qualify parts during production. Powder layer quality was measured in different conditions and changed drastically as a function of recoating speed, preheating temperature but also particle shape. The effective layer thickness was obtained for the first time in PBF of polymers, and gradually increased with the layer count until reaching a plateau at the nominal layer thickness. Powder layer density could be calculated as well and lies between 34 and 65 %, depending on the powder type and layer count. Finally, curling increased with decreasing preheating temperature, ranging from 70 µm to 350 µm i.e. until collision with the recoater. Based on the measured degree of curling, mitigation strategies could be integrated using a closed-loop feedback control. Effective process monitoring such as the one provided with laser profilometry may enable the development of new materials featuring more complex processing conditions, but also larger machines where thermal uniformity might be an issue.

A Portable Servoregulation Controller to Automate CO2 Removal in Artificial Lungs.

Artificial lung (AL) systems provide respiratory support to patients with severe lung disease, but none can adapt to the changing respiratory needs of the patients. Precisely, none can automatically adjust carbon dioxide () removal from the blood in response to changes in patient activity or disease status. Because of this, all current systems limit patient comfort, activity level, and rehabilitation. A portable servoregulation controller that automatically modulates removal in ALs to meet the real-time metabolic demands of the patient is described. The controller is based on a proportional-integral-derivative (PID) based closed-loop feedback control system that modulates sweep gas (air) flow through the AL to maintain a target exhaust gas partial pressure (target or ). The presented work advances previous research by (1) using gas-side sensing that avoids complications and clotting associated with blood-based sensors, (2) incorporating all components into a portable, battery-powered package, and (3) integrating smart moisture removal from the AL to enable long term operation. The performance of the controller was tested in vitro for ∼12 h with anti-coagulated bovine blood and 5 days with distilled water. In tests with blood, the sweep gas flow was automatically adjusted by the controller rapidly (<2 min) meeting the specified tEG level when confronted with changes in inlet blood partial pressure of (p) levels at various AL blood flows. Overall, the removal from the AL showed a strong correlation with blood flow rate and blood p levels. The controller successfully operated continuously for 5 days when tested with water. This study demonstrates an important step toward ambulatory AL systems that automatically modulate removal as required by lung disease patients, thereby allowing for physiotherapy, comfort, and activity.

Long-term deorbiting control for an electrodynamic tether system exploiting periodic solutions

This paper focuses on the nonlinear dynamics and control problem of deorbiting an electrodynamic tethered satellite system in an inclined elliptical orbit. Considering the perturbing Lorenz forces, a set of modified equinoctial elements is employed to describe the slow-varying orbital dynamics. In addition, the fast-varying attitude dynamics of the system is incorporated into dynamic modeling by adopting an assumption of a dumbbell model. To circumvent the difficulties in computation of a real-time optimal control law for a long-term deorbiting process, a compound control scheme is proposed. A time-scale separation method is adopted to facilitate the controller design. In the scheme, a nonlinear optimal control law accounting for system constraints and nonlinear dynamics is first proposed to find an initial nominal periodic orbit without considering the variations of orbital elements. Subsequently, a closed-loop feedback control law based on energy rate is presented to track the periodic solutions for several orbits by considering the overall dynamics. Notably, the periodic solution will be re-computed after each tracking procedure to account for the slow variation in orbital elements. Comparative studies are presented to demonstrate the advantages of the proposed control law in reducing computational costs.

Sensorized Reconfigurable Soft Robotic Gripper System for Automated Food Handling

This article presents a versatile soft robotic gripper system whereby its fingers can be reconfigured into different poses such as scoop, pinch, and claw. This allows the gripper to efficiently and safely handle food samples of different shapes, sizes and stiffness such as uncooked tofu and broccoli floret. The 3D-printed fingers were tested to last up to 25 000 cycles without significant changes in the curvature profile and force output profile. A benchmark experiment was conducted to evaluate the performance of the gripper and state-of-the-art gripping solutions. Capability of versatile soft gripper was optimized by integrating vision and tactile sensing facilities. An object recognition system was developed to identify food samples such as potato, broccoli, and sausage. Position and orientation of food samples were identified and pick-and-place pathway was optimized to achieve the best gripping performance. Flexible tactile sensors were integrated into soft fingers and closed-loop force feedback control system was developed. This allowed the gripper to automatically explore and select the most stable grip pose for different food samples. Integration of vision and force feedback system ensure that objects detected by the system would be firmly gripped. The reconfigurable soft robotic gripper system has been demonstrated to perform high-speed pick-and-place tasks (∼3 s per item) with object recognition system, making it a potential solution to food and grocery supply chain needs.

Dual Closed-Loop Control Strategy on Harmonic Plane for Multiphase Induction Motor With Harmonic Injection Based on Air-Gap Flux Orientation Control

Multiphase motors, compared to three-phase motor, have many advantages, such as multiple degrees of freedom and flexible control. However, if these advantages are used incorrectly, it will increase the loss of the motor and decrease the efficiency. In response to this problem, this article lists the three limiting conditions that make the air-gap flux as quasi-trapezoidal waveform and analyzes the reasons why the traditional method cannot make the air-gap flux perfectly distributed. Therefore, a dual closed-loop feedback control structure on the harmonic plane was proposed. In this article, the feasibility and stability of the proposed method are analyzed. A series of comparative experiments on a seven-phase induction motor with concentrated windings platform is given. Finally, a conclusion that the proposed method not only can achieve a better electromotive force (EMF) waveform but also can increase torque per ampere is drawn.

Blood–brain barrier opening in a large animal model using closed-loop microbubble cavitation-based feedback control of focused ultrasound sonication

Focused ultrasound (FUS) in combination with microbubbles has been established as a promising technique for noninvasive and localized Blood–brain barrier (BBB) opening. Real-time passive cavitation detection (PCD)-based feedback control of the FUS sonication is critical to ensure effective BBB opening without causing hemorrhage. This study evaluated the performance of a closed-loop feedback controller in a porcine model. Calibration of the baseline cavitation level was performed for each targeted brain location by a FUS sonication in the presence of intravenously injected microbubbles at a low acoustic pressure without inducing BBB opening. The target cavitation level (TCL) was defined for each target based on the baseline cavitation level. FUS treatment was then performed under real-time PCD-based feedback controller to maintain the cavitation level at the TCL. After FUS treatment, contrast-enhanced MRI and ex vivo histological staining were performed to evaluate the BBB permeability and safety. Safe and effective BBB opening was achieved with the BBB opening volume increased from 3.8 ± 0.7 to 53.6 ± 23.3 mm3 as the TCL was increased from 0.25 to 1 dB. This study validated that effective and safe FUS-induced BBB opening in a large animal model can be achieved with closed-loop feedback control of the FUS sonication.

Collision Avoidance Problem of Ellipsoid Motion

This paper studies the problem of target control and how a virtual ellipsoid can avoid the static obstacle. During the motion to the target set, the virtual ellipsoid can achieve a motion under collision avoidance by keeping the distance between the ellipsoid and obstacle. We present solutions to this problem in the class of closed-loop (feedback) controls based on Hamilton–Jacobi–Bellman (HJB) equation. Simulation results verify the validity and effectiveness of our algorithm.

A multiscale model of the cardiovascular system that regulates arterial pressure viaclosed loopbaroreflex control of chronotropism, cell-level contractility, and vascular tone.

Multiscale models of the cardiovascular system can provide new insights into physiological and pathological processes. PyMyoVent is a computer model that bridges from molecular- to organ-level function and which simulates a left ventricle pumping blood through the systemic circulation. Initial work with PyMyoVent focused on the end-systolic pressure volume relationship and ranked potential therapeutic strategies by their impact on contractility. This manuscript extends the PyMyoVent framework by adding closed-loop feedback control of arterial pressure. The control algorithm mimics important features of the physiological baroreflex and was developed as part of a long-term program that focuses on growth and biological remodeling. Inspired by the underlying biology, the reflex algorithm uses an afferent signal derived from arterial pressure to drive a kinetic model that mimics the net result of neural processing in the medulla and cell-level responses to autonomic drive. The kinetic model outputs control signals that are constrained between limits that represent maximum parasympathetic and maximum sympathetic drive and which modulate heart rate, intracellular Ca2+ dynamics, the molecular-level function of both the thick and the thin myofilaments, and vascular tone. Simulations show that the algorithm can regulate mean arterial pressure at user-defined setpoints as well as maintaining arterial pressure when challenged by changes in blood volume and/or valve resistance. The reflex also regulates arterial pressure when cell-level contractility is modulated to mimic the idealized impact of myotropes. These capabilities will be important for future work that uses computer modeling to investigate clinical conditions and treatments.

TACAN: The Shaping of Delay Distribution Under Multipath Fading Channel for Industrial IoT Systems

The wireless-enabled Industrial Internet of Things (IIoT) system is promising due to its flexibility and cable-free deployment. The varying fading channel will lead to the random transmission delays and jitters, which are the major challenges hindering the adoption of wireless communication in mission-critical industrial systems. The performance or even the stability of closed-loop feedback control system will degrade severely with such delays and jitters. As a result, the maximum delay margin should be met to guarantee the performance of the IIoT system. Aiming to better satisfy this requirement, a novel concept to shape the delay distribution under the industrial multipath fading channel is proposed in this article. Consequently, a two-layer closed feedback control algorithm, referred as TACAN in this article, is designed through the decoupling of original optimization function, by which the variance of the delay distribution is minimized to improve the reliability and stability of the IIoT systems. The performance of proposed delay shape control method is verified by both the classical Rician channel model and the field measured industrial fading channel responses.

Multi-source information fusion for space gravitational waves detection thrust estimation on orbit

Space Gravitational Wave (GW) detection task puts forward super-low thrust noise for micro-newton propulsion system. Study shows thrust noise can be reduced by thrust closed loop feedback control structure. The effect is determined by thrust estimation accuracy. Traditionally, thrust estimation is realized by electric parameters and thrust estimation equation. However, this way is faced with high thrust estimation error in the low frequency band. Besides, the displacement sensor information of the drag-free control system can also be used for thrust estimation via disturbance observer. However, this way is only effective for low-frequency thrust due to the measurement noise of displacement sensor. A data fusion method is proposed in this paper to enhance thrust estimation accuracy. In this method, the high frequency thrust noise is estimated by electric parameters and thrust estimation equation. Meantime, the low frequency thrust noise is estimated by displacement sensor information and disturbance observer. In this paper, the cusped field thruster is used as the actuator of drag-free control system to simulate. Simulation results show thrust estimation by data fusion can effectively reduce thrust noise in the middle frequency band and enhance stability of satellites compared with that by electric parameters.

Closed Loop Modified SEPIC Converter for Photovoltaic System

The high static gain modified single ended primary coil (MSEPIC) converter is presented in this paper. The proposed converter presents low switch voltage and high efficiency for low input voltage and high output voltage applications. The configuration of MSEPIC converter is presented and analyzed. Closed loop feedback control with PID controller based on triggering system is developed for MSEPIC converter to maintain constant output voltage. Furthermore, the model is integrated with Photovoltaic generator where the input voltage and current depend on the solar irradiation rates. The proposed model is analyzed and simulated in Matlab/Simulink and m-file code. Simulation model is developed with a maximum power at full sun equal to 315 W, which presents efficiency equal to 99.03%. The PID controller works as intended, as the output voltage can approach the expected value. Furthermore, performance and robustness are tested by load variations and set point variations.

Review on Haptic Assistive Driving Systems Based on Drivers’ Steering-Wheel Operating Behaviour

With the availability of modern assistive techniques, ambient intelligence, and the Internet of Things (IoT), various innovative assistive environments have been developed, such as driving assistance systems (DAS), where the human driver can be provided with physical and emotional assistance. In this human–machine collaboration system, haptic interaction interfaces are commonly employed because they provide drivers with a more manageable way to interact with other components. From the view of control system theory, this is a typical closed-loop feedback control system with a human in the loop. To make such a system work effectively, both the driving behaviour factors, and the electrical–mechanical components should be considered. However, the main challenge is how to deal with the high degree of uncertainties in human behaviour. This paper aims to provide an insightful overview of the relevant work. The impact of various types of haptic assistive driving systems (haptic guidance and warning systems) on driving behaviour performance is discussed and evaluated. In addition, various driving behaviour modelling systems are extensively investigated. Furthermore, the state-of-the-art driving behaviour controllers are analysed and discussed in driver–vehicle–road systems, with potential improvements and drawbacks addressed. Finally, a prospective approach is recommended to design a robust model-free controller that accounts for uncertainties and individual differences in driving styles in a haptic assistive driving system. The outcome indicated that the haptic feedback system applied to the drivers enhanced their driving performance, lowered their response time, and reduced their mental workload compared to a system with auditory or visual signals or without any haptic system, despite some annoyances and system conflicts. The driving behaviour modelling techniques and the driving behaviour control with a haptic feedback system have shown good matching and improved the steering wheel’s base operation performance. However, mathematical principles, a statistical approach, and the lack of consideration of the individual differences in the driver–vehicle–road system make the modelling and the controller less robust and inefficient for different driving styles.

Feedback Method of Force Controlled by Electrical Muscle Stimulation Based on Infrared Optical Sensing

The goal of the study was to develop a system that can adjust the electrical muscle stimulation parameters for individuals when sharing experiences with stimulation by sensing the degree of muscle contraction during electrical stimulation. If we do not know the appropriate amount of current for stimulation for an individual, the muscles would not contract as we aimed, and we will not be able to share the experience as we expected. In this study, we presented a system estimating fingertip force as the output of electrical muscle stimulation by monitoring the muscle state based on infrared optical sensing for adjusting electrical muscle stimulation parameters for the individual. We developed a regression model based on support vector regression during electrical stimulation using an infrared optical sensor with seven people's data to estimate the pushing force. The coefficient of determination between the measured pushing force and estimated pushing force was greater than 0.8 and 0.9 for the index and middle fingers, respectively. The system can monitor a feedback value of electrical muscle stimulation fingertip control. The system showed the feasibility of infrared optical sensing for the closed-loop feedback control system of the electrical stimulation parameters for an individual.

Vibrotactile Perception for Sensorimotor Augmentation: Perceptual Discrimination of Vibrotactile Stimuli Induced by Low-Cost Eccentric Rotating Mass Motors at Different Body Locations in Young, Middle-Aged, and Older Adults.

Sensory augmentation technologies are being developed to convey useful supplemental sensory cues to people in comfortable, unobtrusive ways for the purpose of improving the ongoing control of volitional movement. Low-cost vibration motors are strong contenders for providing supplemental cues intended to enhance or augment closed-loop feedback control of limb movements in patients with proprioceptive deficits, but who still retain the ability to generate movement. However, it remains unclear what form such cues should take and where on the body they may be applied to enhance the perception-cognition-action cycle implicit in closed-loop feedback control. As a step toward addressing this knowledge gap, we used low-cost, wearable technology to examine the perceptual acuity of vibrotactile stimulus intensity discrimination at several candidate sites on the body in a sample of participants spanning a wide age range. We also sought to determine the extent to which the acuity of vibrotactile discrimination can improve over several days of discrimination training. Healthy adults performed a series of 2-alternative forced choice experiments that quantified capability to perceive small differences in the intensity of stimuli provided by low-cost eccentric rotating mass vibration motors fixed at various body locations. In one set of experiments, we found that the acuity of intensity discrimination was poorer in older participants than in middle-aged and younger participants, and that stimuli applied to the torso were systematically harder to discriminate than stimuli applied to the forearm, knee, or shoulders, which all had similar acuities. In another set of experiments, we found that older adults could improve intensity discrimination over the course of 3 days of practice on that task such that their final performance did not differ significantly from that of younger adults. These findings may be useful for future development of wearable technologies intended to improve the control of movements through the application of supplemental vibrotactile cues.