Multiple DSP system for real time parallel processing and feedback control on fusion experiments

Real-Time Feedback Control of Carbon Content of Zirconium Dioxide Thin Films Using Optical Emission Spectroscopy

Optimization of jet engine sprays has the potential to improve efficiency and reduce environmental impact. Sprays can be continually optimized in multivariate scenarios using real-time feedback control, but a method of controlling the sprays based on physical properties must first be established. In this study, a spray controller was developed to optimize the spray angle obtained from shadowgraphs, with the assumption that the largest angle is desired. The spray angle was used as an example, as it is a physically important parameter which is easily found through shadowgraph imaging. Varying ratios of swirled air to straight air, determined by the image-based feedback controller were introduced into the air portion of a coaxial airblast nozzle while keeping the total air flow rate constant. A golden section search converged on the swirled air ratio that provided the largest angle and was validated from the distribution of spray angle versus swirled air ratio. The ratio that produced a spray with the greatest angle of 25.8 ± 2 deg was found at a swirled air ratio of 0.66 ± 0.03 for a spray with a momentum ratio of 6. The successful design and implementation of this image-based feedback controller is intended to provide a foundation for developing real-time active feedback controllers for sprays.

Goal: Assess performance and potential use of a novel, servo-controlled, gravity-driven infusion device with FDA regulatory clearance obtained 3/1/2024(K242693). Introduction: "SAFEflowTM" (SF) using real time flow measurement and feedback control, has been cleared by USFDA. We hypothesized that due to its architecture using video imaging there will be both benefits, and functional contrasts with the behavior of legacy infusion pumps (LIPs). Methods: We conducted type-tests of critical metrics using AAMI and IEC standards together with computational simulations. Results were compared with claimed and measured performance of two widely-used LIPs. Results/Discussion: Across its rated flow range of 1-600 ml h−1, SF’s measured flow performance was superior (95/95% confidence/reliability −4.3% to +4.5% mean flow rate accuracy) to claims of two LIP designs, Occlusion detection was more consistent and rapid across flow rates and requiring less user interaction. Conclusion: SF’s infusion performance was superior with reduced weight, size, and low parts count compared to LIPs. Regulatory evaluation standards may require updating for this class of infusion device.

Dielectric barrier discharge plasma actuators (DBD-PA) and fiber Bragg grating flow sensors (FBG-FS) have been investigated for active control of flow separation around a NACA0024 airfoil. Tangential jets were produced in the vicinity of the DBD-PA slightly aft of the leading edge of the airfoil. The flow separation control ability was evaluated at a low Reynolds number, Re = 5.0×104, in an open-circuit wind tunnel. Analysis of instantaneous and time-averaged velocity distributions around the airfoil was achieved using a particle image velocimetry (PIV) system. The flow conditions induced by the DBD-PA to suppress the flow separation were found for angles of attack of α = 8°, 12°, and 16°. When unaided by the DBD-PA system, flow separations from NACA0024 airfoil are suppressed significantly for certain Reynolds numbers and angles of attack. FBG-FS attached a chord-wise cantilever near the trailing edge of the airfoil was used to measure strain fluctuations for its feasibility to detect flow separation in real time and construct feedback control system with DBD-PA. In this study, it was found that standard deviations of strain fluctuations increase obviously in cases of flow conditions at which the flow around NACA0024 airfoil separates.

NEW DIII-D TOKAMAK PLASMA CONTROL SYSTEM

Implementation of real-time and in-line feedback control for a fluid bed granulation process.

As integrated circuit feature size continues to shrink, yield loss due to parametric variation will become more and more significant. Real-time feedback control provides a means of reducing parametric variation and therefore limiting this type of yield loss. A challenge in applying feedback control to semiconductor manufacturing processes is selecting the variables to feed back. In many manufacturing processes, the important product variables cannot be measured in real-time and therefore cannot be directly controlled using real-time feedback control. An alternative, which has proven effective, is to feed back process variables closely related to the product variables. Typically, selection of process variables to feed back is based upon qualitative knowledge about the process, which in many cases is limited. In this paper, an empirical methodology for selecting the best process variables for feedback in order to minimize variation in the product variables is presented. Two versions of this methodology are described, a full version and a "lite" version. The latter is an abridged version of the former. Prior to introducing this methodology, a condition under which real-time feedback control will reduce product variable variation is derived. This condition is used to highlight the sources of variance in the product variables, information which is used to explain how the methodology works. The methodology is evaluated using simulated experiments. Both the full and lite versions prove to be effective under the assumptions stated for this study although the full version is clearly superior in terms of performance. Application of the methodology to a reactive ion etch process is described in a companion work.

To overcome productivity issues and revolutionize the stagnating construction industry, a large amount of research efforts has been devoted to robot-assisted construction technology. The advancements in robotics including mechanical system design, tool design, digital system design, and numerical control systems design enabled engineers to create complex geometries that are infeasible for conventional construction methods. In addition, innovative robotic systems that utilize mobile platforms, multiple robots, and unmanned aerial vehicles have demonstrated significant promise in fully automating the construction process. This work will provide a perspective on the state-of-the-art applications of robotics in the revolution of construction, where a comprehensive review of the current development of the relevant software and hardware, 3D concrete printing (3DCP), robot-assisted assembly of discrete prefabricated blocks, real-time quality monitoring and feedback control systems, and typical innovative robot-assisted structural designs are conducted. Finally, the limitations of existing robot-assisted construction technology are identified, which leads to several recommendations for future research toward fully automatic construction.

During retinal microsurgery, surgeons cannot adequately visualize subsurface anatomical structures. In our previous work, a customized B-mode optical coherence tomography (OCT) probe was integrated into an ophthalmic robotic system to provide depth perception. This paper presents new approaches for implementing and achieving real-time feedback and assistive robotic control based on B-mode OCT imaging. The robotic system was comprised of a parallel robot, a micro-injection tool, and a telemanipulation master interface. A method for calibrating the B-mode OCT image scaling and distortion was presented using thin plate splines. Determining the OCT scanning plane relative to the robot base frame is presented through experiments and analyzed for sensitivity. A dual-rate controller using low frequency OCT feedback and high frequency position servoing was presented and tested for accuracy and latency. Three-dimensional assistive telemanipulation virtual fixtures based on microscope and OCT feedback are presented. The experimental evaluation demonstrated following target anatomy and semi-automated micro-injection. These results present the key steps towards achieving an integrated system for OCT feedback control using a miniature intraocular B-mode probe.

A two-stage iterative learning control technique combined with real-time feedback for independent disturbance rejection

Focused ultrasound combined with bubble-based agents serves as a non-invasive way to open the blood-brain barrier (BBB). Passive acoustic detection was well studied recently to monitor the acoustic emissions induced by the bubbles under ultrasound energy, but the ability to perform reliable BBB opening with a real-time feedback control algorithm has not been fully evaluated. This study focuses on characterizing the acoustic emissions of different types of bubbles: Optison, Definity, and a custom-made nanobubble. Their performance on reliable BBB opening under real-time feedback control based on acoustic detection was evaluated both in-vitro and in-vivo. The experiments were conducted using a 0.5 MHz focused ultrasound transducer with in-vivo focal pressure ranges from 0.1–0.7 MPa. Successful feedback control was achieved with all three agents when combining with infusion injection. Localized opening was confirmed with Evans blue dye leakage. Microscopic images were acquired to review the opening effects. Under similar total gas volume, nanobubble showed a more reliable opening effect compared to Optison and Definity (p < 0.05). The conclusions obtained from this study confirm the possibilities of performing stable opening using a feedback control algorithm combined with infusion injection. It also opens another potential research area of BBB opening using sub-micron bubbles.

In this paper, a real-time location feedback control system based on multi-sensor network is proposed for the precise control of a moving robot. The target tracking network system is a real test-bed that consists of a group of ultrasonic sensor nodes, a mobile robot and two laptops. In order to pursue excellent tracking performance and modify the robot’s trajectory promptly, Extended Kalman Filtering algorithm as well as a kind of scheduling scheme based on location is applied in the system. The experiment result validates the correctness of the Extended Kalman Filter (EKF) and shows that the target tracking network system is effective for robot feedback control.

The J-TEXT newly deployed three-wave polarimeter-interferometer (POLARIS) system provides a better time and spatial resolution of the plasma electronic density than the old HCN interferometer system. The plasma electron density feedback control system is implemented on the already existing POLARIS DAQ system which is based on FlexRIO FPGA. Another FlexRIO board with an output module is added to implement the feedback control algorithm and feed the output to the piezoelectric crystal valve. The density feedback control system is able to extract the phase difference information from the intermedia frequency signal using FFT, calculate density of multiple channels and output control signal to the piezoelectric crystal valve in real-time. NI P2P technology is used to transfer processed data from a FlexRIO board to another in real-time without using the CPU. This system is also able to calculate density profile. With the density profile it can use compensated central chord line integrated or average density as control target. Also the real-time density profile data is useful for future plasma control system and disruption detection system.

We propose an algorithm for nonlinear receding-horizon output feedback control by combining a real-time nonlinear optimal state feedback control algorithm and a real-time nonlinear optimal state estimation algorithm. The algorithms of state feedback control and state estimation are obtained by minimizing receding-horizon performance indexes. Application of the stabilized continuation method results in algorithms that do not involve any successive approximation methods. Simulation results of a 2-wheeled car clarify characteristics of the output feedback control algorithm.

A TWO-STAGE ALGORITHM FOR COMBINED ITERATIVE LEARNING CONTROL WITH REAL-TIME FEEDBACK; A STATE SPACE FORMULATION