Sensor Feedback Control Research Articles

Convolutional neural network augmented soft-sensor for autonomous microfluidic production of uniform bubbles

Microfluidics has emerged as a foundational process for creating highly uniform emulsions and bubbles. To enable integration of microfluidic platforms into industrial processes, achieving precise control over the size uniformity of microfluidic-generated bubbles and emulsions is crucial. Even if the external variables such as flow rates or pressures are kept constant, microfluidic processes can be easily disturbed by unknown factors that would substantially compromise the uniformity of resulting emulsions and bubbles. In this study, we introduce a two-step soft-sensor approach that combines a convolutional neural network (CNN) and an image recognition algorithm for feature extraction to detect both the flow regime and the size and uniformity of resulting bubbles. By using a CNN to detect flow regimes, our controller is able to restore the bubble-producing flow regime in response to disturbances. Beyond self-recovery, our controller actively adjusts to minimize errors, maintain setpoints, mitigate disturbances, and ensure system stability over extended periods. 99.2% of bubbles produced during an 8-hour period remain within 5% of the setpoint with our controller acting. By leveraging the soft sensor and artificial intelligence-assisted feedback control, our work presents a widely applicable approach for precise and automated control of microfluidics in diverse applications.

Soft crawling robot integrated with liquid metal-based flexible strain sensor and closed-loop feedback control

Due to the inherent softness and adaptability, soft robots have shown great application prospects in medical rehabilitation, environmental exploration, and other fields. However, the unpredictable and complex behaviors of the elastic materials greatly increased the difficulty in the control of soft robots. This study proposed an integrated soft crawling robot (ISCR) with flexible strain sensors to achieve the closed-loop feedback control of motion. First, a flexible strain sensor was fabricated by injecting liquid metal (LM) into an elastomer with a wavy structure. The key performances of the sensor were investigated. The developed flexible strain sensor can achieve a high gauge factor of 2.07, a low hysteresis of 1.902%, a wide detection range of 150% strain, a low detection limitation as low as 0.4% strain change, and an excellent stability and durability, which fully satisfy the requirements for the proprioception of soft robots. We built a closed-loop feedback control system to achieve closed-loop control of the ISCR. Finally, we successfully realized the continuous motion of the ISCR under closed-loop control. We believe this work will be helpful for the development of automation and intelligence of soft crawling robots.

Integrated intelligent tactile system for a humanoid robot

Tactile perception is the basis of human motion. Achieving artificial tactility is one of the challenges in the fields of smart robotics and artificial intelligence (AI), because touch emulation relies on high-performance pressure sensor arrays, signal reading, information processing, and feedback control. In this paper, we report an integrated intelligent tactile system (IITS) that is integrated with a humanoid robot to achieve human-like artificial tactile perception. The IITS is a closed-loop system that includes a multi-channel tactile sensing e-skin, a data acquisition and information processing chip, and a feedback control. With customized preset values of threshold pressures, the IITS-integrated robot can flexibly grasp various objects. The IITS has potential applications in the design of prosthetic hands, space manipulators, deep-sea exploration robots, and human-robot interactions.

Design, Construction and Control of an Autonomous Mobile Rescue Robot with Visual Feedback

The construction of a smart autonomous mobile robot system that can operate in an anonymous environment can be difficult. Building an autonomous mobile robot requires collecting data from sensors and cameras in order to recognize the surrounding environment, get knowledge of existing landmarks, and figure out its position and orientation. Many research studies have been carried out in recent years providing algorithms for achieving autonomous motion of mobile robot systems and object detection. The most common platform utilized for robot motion design is ROS (Robot Operating System) and for object detection YOLO (You Only Look Once) is a common choice. Additionally, the autonomous system needs motion planning in a systematic way to avoid obstacles by using LIDAR or other sensing methods generating the feedback signals required for control of motion around occupied spaces. One of the most effective and versatile feedback systems for mobile robot control can be constructed using visual feedback, which relies on a high-resolution camera that processes the image in real-time and the result is fed back to the control system for decision making. Visual feedback can be employed alone without sensors for feedback control of autonomous mobile robots, and it can be used for multiple tasks like path planning, obstacle avoidance, object detection, object recognition in addition to motion control. In this research, results of design and construction of an autonomous mobile rescue robot for finding victims through video data are presented. It is aimed to find victims via applying video as a data collection and feedback generation tool in the autonomous mobile robot control system. The visual feedback and YOLO v3 are used not only for finding victims but also for motion control. Our autonomous mobile robot is designed to move smoothly to the victim's direction and avoids obstacles by using ROS Global Planner. The robot is tested in multiple scenarios in different locations, various obstacle and victim numbers, and satisfactory results with good performances are obtained.

Feedback control of a pneumatically driven soft finger using a photoelastic polyurethane bending sensor

ABSTRACT In recent years, pneumatically driven soft-fingered hands constructed from polymer materials have been developed to grasp variously shaped objects. In general, the motion-control ability of these hands is limited to grasping objects. A dexterous manipulation requires pinching and in-hand manipulation. However, this is difficult because soft-fingered hands face two major problems of low positioning accuracy and vibration during high-speed motion. These problems can be solved with feedback control by using a soft sensor that does not impair finger softness. This study proposes a pneumatically driven soft-finger system with a soft-position sensor formed from photoelastic polyurethane that measures the soft-finger curvature through changes in the light intensity. A sensor feedback control for the soft finger is also established in this paper. Consequently, in a series of basic experiments, the sensor feedback control achieved precise positioning and continuous accurate path tracking. Finally, pinching motions and object orientation control were achieved by accurate continuous-path control of two soft fingers.

Modelling of minor hysteresis loop of shape memory alloy wire actuator and its application in self-sensing

Shape memory alloy (SMA) wire actuators offer large force and displacement capabilities out of the stress and temperature-dependent martensitic phase transformation. Among the various modelling approaches in the literature, the one proposed by Boyd and Lagoudas (1996), is mostly used in analysing SMA based components. In practice, partial actuation is often required and is enacted by aborting and subsequently resuming the phase transformation; exhibiting minor hysteresis response. The existing models are found to be inaccurate in simulating such partial transformation cases. In this study, a novel yield parameter, which depends on the martensite volume fraction, has been proposed; enabling the model of Boyd and Lagoudas to simulate minor hysteresis loop accurately. The corresponding model parameters are derived, satisfying certain practical aspects of the SMA response. Using the modified model, pseudoelastic responses are simulated for different partial loading cases and are compared against the same obtained from the existing models, illustrating its efficacy. Following the proposed model, the discrete form of the system dynamics of a SMA wire actuator is formulated. Using this, an extended Kalman filter (EKF) has been developed, to estimate the output of the system from the change in electrical resistance of the SMA wire during actuation. This approach eliminates the requirement of external sensors for feedback control. Using the developed EKF, the response of an SMA wire actuated system is estimated from the experimentally measured electrical resistance data of the SMA wire and are compared with the corresponding measured responses. The results reveal that a significant level of accuracy can be achieved with the proposed approach.

Measurement of Contractile Force of Artificial Muscle using Soft Sensor for Feedback Control of bio-actuator

Measurement of Contractile Force of Artificial Muscle using Soft Sensor for Feedback Control of bio-actuator

Robust Set-Invariance Based Fuzzy Output Tracking Control for Vehicle Autonomous Driving Under Uncertain Lateral Forces and Steering Constraints

This paper is concerned with a new control method for path tracking of autonomous ground vehicles. We exploit the fuzzy model-based control framework to deal with the time-varying feature of the vehicle speed and the highly uncertain behaviors of the tire-road forces involved in the nonlinear vehicle dynamics. To avoid using costly vehicle sensors for feedback control while favoring the simplest control structure for real-time implementation, a new fuzzy static output feedback (SOF) scheme is proposed. In particular, though the robust set-invariance property and Lyapunov-based arguments, the physical constraints on the steering input saturation and the vehicle state can be taken into account in the control design to improve the driving safety and comfort. The theoretical development relies on the use of fuzzy Lyapunov functions and the non-parallel distributed compensation control concept to reduce the design conservatism. Exploiting some specific convexification techniques, the control design is reformulated as an optimization problem under linear matrix inequalities with a single line search, which are efficiently solved via semidefinite programming techniques. The proposed fuzzy path tracking controller is evaluated through various dynamic driving tests conducted with high-fidelity CarSim/Matlab co-simulations. Moreover, to emphasize the advantages of the new fuzzy SOF controller, a performance comparison with the CarSim driver model is also performed.

Image-based visual servoing improvement through utilization of adaptive control gain and pseudo-inverse of the weighted mean of the Jacobians

The use of information acquired by stationary or onboard vision sensors for feedback control of pose and motion of a robot is known as visual servoing. In this paper, an image-based visual servoing controller with improved rate and domain of convergence is presented using adaptive control gain and pseudo-inverse of the weighted mean of the Jacobians. Furthermore, the stability of the proposed controller is proved by means of Lyapunov criteria, and simulations results are provided to demonstrate the validity and advantages of this control scheme. In comparison with the pseudo-inverse of the mean of the Jacobians scheme, the proposed controller increased the convergence rate of the servoing system up to seven times when used in complex motion tasks, and widened the convergence domain of the system up to 179° initial camera yaw angle when used in pure rotation tasks.

Active multimode vibration control of a smart structure using macro fiber composite actuators based on ANFIS

In this study, vibration control was achieved using macro fiber composite actuators initiated by feedback from polyvinylidene difluoride (PVDF) membrane sensors. First, the structure mode was found using the finite element method after which simulation of the effect of piezoelectric actuators on the structure as well as a feasibility investigation was carried out. The ANSYS Workbench was used for parametric design and to determine the best position for the actuators. Structure vibration in different modes was measured using PVDF membrane sensors for feedback control and to investigate the vibration reduction effect achieved with three individual controllers. The pros and cons of active vibration reduction control were also examined in several different modes. The experimental results obtained with several types of vibration reduction control were compared: Type-1 fuzzy control, Type-1 adaptive fuzzy control, and the vibration reduction effect of an adaptive neuro-fuzzy inference system. The results showed that the adaptive neuro-fuzzy inference system controller was the best choice under the experimental conditions used in this study.

Evaluation of a novel flow-controlled syringe infusion pump for precise and continuous drug delivery at low flow rates: a laboratory study.

Syringe infusion pumps are used for the administration of short-acting drugs in anaesthesia and critical care medicine, but are prone to flow irregularities at low flow rates. A flow-controlled syringe infusion pump using an integrated flow sensor for feedback control represents a new approach to overcoming these limitations. This study compares the performance of a prototype flow-controlled syringe pump both at start-up, and during vertical displacement manoeuvres, with that of a standard infusion syringe pump. The novel pump almost completely eliminated delays at start-up and flow irregularities during hydrostatic pressure changes. Related fluctuations in plasma drug concentration were minimised and the known disadvantages of standard syringe infusion pumps currently used in clinical practice were reduced. Besides providing fast start-up to steady-state flow and precise continuous drug delivery at low flow rates during hydrostatic pressure changes, the new pump offers the potential for the development of target-controlled infusion algorithms for short-acting cardiovascular and other drugs.

Fog computing with original data reference function

In recent years, since large amounts of data are being transferred to the cloud server because of the evolution of the Internet of Things (IoT), problems such as the network bandwidth restrictions and sensor feedback control delays have appeared. For these limitations, fog computing, in which the primary processing of sensor data is performed at the fog node, and only the results are transferred to the cloud server, has been proposed. However, in this method, when the original sensor data are necessary for the analysis in the cloud server, the data are missing. For this problem, I propose a data model, in which the original sensor data are stored at the fog node with a distributed database. Furthermore, the performance of this data model is evaluated, showing the original data reference from the cloud server can be executed efficiently, particularly in the case of installing multiple fog nodes.

Fog computing with original data reference function

In recent years, since large amounts of data are being transferred to the cloud server because of the evolution of the Internet of Things (IoT), problems such as the network bandwidth restrictions and sensor feedback control delays have appeared. For these limitations, fog computing, in which the primary processing of sensor data is performed at the fog node, and only the results are transferred to the cloud server, has been proposed. However, in this method, when the original sensor data are necessary for the analysis in the cloud server, the data are missing. For this problem, I propose a data model, in which the original sensor data are stored at the fog node with a distributed database. Furthermore, the performance of this data model is evaluated, showing the original data reference from the cloud server can be executed efficiently, particularly in the case of installing multiple fog nodes.

Ultrasonic sensor concept to fit a ventricular assist device cannula evaluated using geometrically accurate heart phantoms.

Future left ventricular assist devices (LVADs) are expected to respond to the physiologic need of patients; however, they still lack reliable pressure or volume sensors for feedback control. In the clinic, echocardiography systems are routinely used to measure left ventricular (LV) volume. Until now, echocardiography in this form was never integrated in LVADs due to its computational complexity. The aim of this study was to demonstrate the applicability of a simplified ultrasonic sensor to fit an LVAD cannula and to show the achievable accuracy in vitro. Our approach requires only two ultrasonic transducers because we estimated the LV volume with the LV end-diastolic diameter commonly used in clinical assessments. In order to optimize the accuracy, we assessed the optimal design parameters considering over 50 orientations of the two ultrasonic transducers. A test bench was equipped with five talcum-infused silicone heart phantoms, in which the intra-ventricular surface replicated papillary muscles and trabeculae carnae. The end-diastolic LV filling volumes of the five heart phantoms ranged from 180 to 480 mL. This reference volume was altered by ±40 mL with a syringe pump. Based on the calibrated measurements acquired by the two ultrasonic transducers, the LV volume was estimated well. However, the accuracies obtained are strongly dependent on the choice of the design parameters. Orientations toward the septum perform better, as they interfere less with the papillary muscles. The optimized design is valid for all hearts. Considering this, the Bland-Altman analysis reports the LV volume accuracy as a bias of ±10% and limits of agreement of 0%-40% in all but the smallest heart. The simplicity of traditional echocardiography systems was reduced by two orders of magnitude in technical complexity, while achieving a comparable accuracy to 2D echocardiography requiring a calibration of absolute volume only. Hence, our approach exploits the established benefits of echocardiography and makes them applicable as an LV volume sensor for LVADs.

A microfluidic relative permittivity sensor for feedback control of carbon dioxide expanded liquid flows

Binary CO2-alcohol mixtures, such as CO2-expanded liquids (CXLs), are promising green solvents for reaching higher performance in flow chemistry and separation processing. However, their compressibility and high working pressure makes handling challenging. These mixtures allow for a tuneable polarity but, to do so, requires precise flow control. Here, a high-pressure tolerant microfluidic system containing a relative permittivity sensor and a mixing chip is used to actively regulate the relative permittivity of these fluids and indirectly—composition. The sensor is a fluid-filled plate capacitor created using embedded 3D-structured thin films and has a linearity of 0.9999, a sensitivity of 4.88 pF per unit of relative permittivity, and a precision within 0.6% for a sampling volume of 0.3 μL. Composition and relative permittivity of CO2-ethanol mixtures were measured at 82 bar and 21 °C during flow. By flow and dielectric models, this relationship was found to be described by the pure components and a quadratic mixing rule with an interaction parameter, kij, of -0.63 ± 0.02. Microflows with a relative permittivity of 1.7–21.4 were generated, and using the models, this was found to correspond to compositions of 6–90 mol % ethanol in CO2. With the sensor, a closed loop control system was realised and CO2-ethanol flows were tuned to setpoints of the relative permittivity in 30 s.

Compensation of the pick-up fluxes on the plasma position control system when resonant magnetic perturbations are applied in J-TEXT.

In the J-TEXT tokamak the displacement coils, which serve as sensors for feedback control of plasma position, are significantly affected by the resonant magnetic perturbation (RMP) coils. To eliminate the deviation of plasma position caused by the RMP, the responses of the displacement coils to the RMP are studied with a view to compensate for the pick-up fluxes. Both the linear and eddy responses on the displacement coils are taken into account and adjusted accordingly. It was found that positional correction in the vertical direction was required when the RMP was operated in the poloidal mode m = 1 and horizontal positional correction was required when the RMP was operated in the m = 2 mode. When compensation was applied to the position control system, correction of plasma position was successfully achieved, as observed from soft X-ray imaging, as well as from the evolution of the current of the horizontal and vertical fields.

Teach‐and‐repeat path following for an autonomous underwater vehicle

AbstractThis paper presents a teach‐and‐repeat path‐following method for an autonomous underwater vehicle (AUV) navigating long distances in environments where external navigation aides are denied. This method utilizes sonar images to construct a series of reference views along a path, stored as a topological map. The AUV can then renavigate along this path, either to return to the start location or to repeat the route. Utilizing unique assumptions about the sonar image‐generation process, this system exhibits robust image‐matching capabilities, providing observations to a discrete Bayesian filter that maintains an estimate of progress along the path. Image‐matching also provides an estimate of offset from the path, allowing the AUV to correct its heading and effectively close the gap. Over a series of field trials, this system demonstrated online control of an AUV in the ocean environment of Holyrood Arm, Newfoundland and Labrador, Canada. The system was implemented on an International Submarine Engineering Ltd. Explorer AUV and performed multiple path completions over both a 1 and 5 km track. These trials illustrated an AUV operating in a fully autonomous mode, in which navigation was driven solely by sensor feedback and adaptive control. Path‐following performance was as desired, with the AUV maintaining close offset to the path.

Atomic force microscopy capable of vibration isolation with low-stiffness Z-axis actuation

For high-resolution imaging without bulky external vibration isolation, this paper presents an atomic force microscope (AFM) capable of vibration isolation with its internal Z-axis (vertical) actuators moving the AFM probe. Lorentz actuators (voice coil actuators) are used for the Z-axis actuation, and flexures guiding the motion are designed to have a low stiffness between the mover and the base. The low stiffness enables a large Z-axis actuation of more than 700 µm and mechanically isolates the probe from floor vibrations at high frequencies. To reject the residual vibrations, the probe tracks the sample by using a displacement sensor for feedback control. Unlike conventional AFMs, the Z-axis actuation attains a closed-loop control bandwidth that is 35 times higher than the first mechanical resonant frequency. The closed-loop AFM system has robustness against the flexures’ nonlinearity and uses the first resonance for better sample tracking. For further improvement, feedforward control with a vibration sensor is combined, and the resulting system rejects 98.4% of vibrations by turning on the controllers. The AFM system is demonstrated by successful AFM imaging in a vibrational environment.

A Large-Stroke 3DOF Stage With Integrated Feedback in MEMS

In this paper, we design, fabricate, and validate a large-stroke 3-degree-of-freedom (DOF) positioning stage with integrated displacement sensors for feedback control in a single-mask microelectromechanical systems (MEMS) fabrication process. Three equal shuttles exactly define the position of the stage in $x$ , $y$ , and $R_{z}$ . The kinematic relation between the shuttle positions and the stage position is given by the geometric transfer function. By increasing the order of this geometric transfer function, the stage error can be reduced. Each shuttle consists of a flexure mechanism, a position sensor, and electrostatic comb drive actuators for actuation along a straight line. The range of motion of the stage is limited by electrostatic pull-in of these comb drives. Three parameters of the stage, the leafspring length, the eccentricity, and the tangential arm, have been varied to find their influence on the stage range of motion. These simulation results can be used to design stages with different specifications. Position control of the individual shuttles is applied to control the position of the stage. The stroke of the 3DOF stage is verified up to 161 $\mu \text{m}$ in $x$ , 175 $\mu \text{m}$ in $y$ , and 325 mrad in $R_{z}$ . This exceeds the range of motion of existing stages. [2014-0314]

Developing of Fuzzy Logic Controller for Air Condition System

uzzy logic control was developed to control the compressor motor speed , fan speed , fin direction and operation mode to maintain the room temperature at or closed to the set point temperature and save energy and keep devices from damage. This paper describes the development of Fuzzy logic algorithm for Air Condition control system. This system consists of four sensors for feedback control: first for input electric volt which used to save devices from damage due to alternated voltages, second for temperature and third for humidity and fourth for dew point. Simulation of the Fuzzy logic algorithm for Air Condition controlling system is carried out based on MATLAB.