A rule-based phase control methodology for a slider-crank wave energy converter power take-off system
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Sang, Yuanrui↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Robust cooperative control strategy for a platoon of connected and autonomous vehicles against sensor errors and control errors simultaneously in a real-world driving environment
In a real-world driving environment, a platoon of connected and autonomous vehicles (CAVs) is subject to many internal and external disturbances, resulting in uncertain vehicle dynamics. In general, the disturbances can be categorized into two types: disturbances due to vehicle sensor errors (e.g., GPS error) and disturbances due to vehicle control errors (e.g., actuator delay). In the literature, many control strategies have been proposed to improve the robustness of the CAV platoon against uncertain vehicle dynamics induced by these disturbances. However, most of these strategies only consider one type of disturbance and cannot tackle both types of disturbances simultaneously. Furthermore, they are designed to maximize the benefits of each vehicle in the platoon independently, which can deteriorate the performance of the platoon. Here, to address these problems, this study proposes a robust cooperative control (RCC) strategy to maneuver the vehicles in the platoon cooperatively to counteract the impacts of both types of disturbances. The RCC strategy is developed based on a minimax problem, where the maximization subproblem seeks to find the worst inputs for the uncertainty terms in the vehicle dynamics equation to minimize the platoon performance, while the minimization subproblem seeks to find the optimal control decisions for all subsequent vehicles to maximize the platoon performance in the worst case. To solve the minimax problem, this study proposes a globally convergent solution algorithm. It can solve the minimax problem very efficiently to enable real time deployment of the RCC strategy. Numerical application indicates that compared to the existing methods, the RCC strategy can dramatically improve the robustness of the CAV platoon against the uncertain vehicle dynamics induced by both vehicle state detection errors and vehicle control errors. Therefore, it can maneuver the CAV platoon safely and efficiently in a real-world driving environment.
33 ADVANCED PROPULSION SYSTEMS↗
Engineering microbial consortia for controllable outputs
Much research has been invested into engineering microorganisms to perform desired biotransformations; nonetheless, these efforts frequently fall short of expected results due to the unforeseen effects of biofeedback regulation and functional incompatibility. In nature, metabolic function is compartmentalized into diverse organisms assembled into resilient consortia, in which the division of labor is thought to lead to increased community efficiency and productivity. Here, we consider whether and how consortia can be designed to perform bioprocesses of interest beyond the metabolic flexibility limitations of a single organism. Advances in post-genomic analysis of microbial consortia and application of high-resolution global measurements now offer the promise of systems-level understanding of how microbial consortia adapt to changes in environmental variables and inputs of carbon and energy. We argue that when combined with appropriate modeling framework that predictive knowledge generates testable hypotheses and orthogonal synthetic biology tools, such understanding can dramatically improve our ability to control the fate and functioning of consortia. In this article, we articulate our collective perspective on the current and future state of microbial community engineering and control while placing specific emphasis on ecological principles that promote control over community function and emergent properties.
controllable outputs↗
Control of formation of viscoelastic droplets and distribution of nano-inclusions in functional deposition for lithium–sulfur batteries
The electrospray process produces micro/nanodroplets for various applications such as thin and uniform coatings, drug carriers and mass spectrometry. In this paper, we study the spray processes of viscoelastic jets using simulations and experiments. In discretized modeling, the jet is perturbed with axisymmetric instability and the growth of this instability causes the jet to break into droplets. For the experiments, a solution of polyvinyl alcohol in water is sprayed and is visualized using a high-speed camera. The droplet size distribution is studied from simulations with experiments for three spray cases: electrospray, air spray, and air-controlled electrospray. Our simulations and experiments reveal that the electric field is effective in reducing the droplet size, while air flow offers more jet break-ups and thus a larger number of droplets. As a result, air-controlled electrospray where these two driving forces are synergistically combined leads to a larger number of smaller droplets than electrospray or air spray. As a result, we applied three spray processes to obtain a deposition of sulfur/mesoporous carbon/graphene/polymer binder composites as a lithium sulfur battery cathode and demonstrated that air-controlled electrospray leads to a higher capacity and rate capability than other processes, exhibiting 800 mA h g –1 at 0.5C and 600 mA h g –1 at 2C.
25 ENERGY STORAGE↗
Traffic Signal Control for Large-Scale Urban Traffic Networks: Real-World Experiments using Vision-Based Sensors
Effective control of traffic signals plays a critical role in ensuring smooth vehicle flow in urban areas. Expertly engineered traffic signal controllers can considerably minimize travel delays and enhance sustainability. In this paper, the team proposes the Model Predictive Control (MPC) traffic signal control strategy using real-time traffic flow data from a vision-based camera as feedback information. Also, a realistic signal timing plan that considers National Electrical Manufacturers Association (NEMA) constraints has been developed to be applied to real-world scenarios. The primary aim is to reduce the number of vehicles across all links in the controlled area, thereby optimizing traffic flow and reducing energy consumption. To validate the proposed method, several real-life experiments were conducted at 24 intersections in Chattanooga, Tennessee, by collaborating with traffic field engineers. These experiments demonstrated significant performance improvements in comparison to the existing method.
data processing↗
Phasor Based Control with the Distributed, Extensible Grid Control Platform
This paper describes how to implement Phasor Based Control (PBC) using the Distributed, Extensible Grid Control (DEGC) Platform. PBC is a novel method for controlling distributed energy resources (DER) that coordinates a centralized optimization with distributed feedback controllers to enforce voltage phasor targets. DEGC is an open source software and communication platform designed for general DER control. We deployed PBC at Lawrence Berkeley Lab's FLEXLAB test site, conducting multiple hardware-in-the-loop test runs. Here, we describe how DEGC was used to implement PBC on hardware, and results demonstrating successful deployment.
24 POWER TRANSMISSION AND DISTRIBUTION↗
An Inrush Current Limiting Strategy for Virtual-Oscillator-Controlled Grid-Forming Inverters
Not provided.
Energy & Fuels↗
Fuzzy Controllers in the Adaptive Control System of a CNC Lathe
Traditional approaches to improving the technological system of CNC metal-cutting machines include increasing the rigidity, periodic maintenance and repair of its components, and operating at lower speeds. In practice, the most economical approach is stabilization of the inputs to the system. The development of adaptive control systems with stabilization of the cutting forces improves the precision and quality of machining in CNC metal-cutting machines, the productivity, and tool life. However, classical PID controllers are only effective in stabilizing the cutting forces in such systems if continuous real-time parameter adjustment is possible. That sharply increases the complexity of the controller. A new mathematical apparatus based on artificial intelligence (including fuzzy logic) permits the solution of adaptive control problems that previously could hardly even be formulated. The present work addresses the use of fuzzy logic in automatic stabilization of the cutting force for CNC lathes. Simulation of a fuzzy controller shows that this approach to automatic stabilization of the cutting force increases the machining efficiency on existing equipment with indeterminacy in the characteristics of the cutting system and the working environment.
42 ENGINEERING↗
Experimental Investigation of Temperature Feedback Control Systems Applicable to Turbojet-engine Control
Temperature - fuel-flow and temperature-area feedback control systems were investigated as means of controlling tailpipe gas temperature of a turbojet engine during transient operation in the high-speed region. Proportional-plus-integral control was used in both systems, but in the temperature-area control system it was necessary to add nonlinear components to the basic proportional-plus-integral control to provide satisfactory transient response to a desired step increase in temperature. Time integral of temperature-error functions were used as criteria for determining optimum transient response. A description of engine dynamics was obtained from frequency-response data.
ENGINES, TURBOJET↗
Task Demand Variation in Air Traffic Control: Implications for Controller Workload, Fatigue, and Performance
In air traffic control, task demand and workload have important implications for the safety and efficiency of air traffic, and remain dominant considerations. Within air traffic control, task demand is dynamic. However, research on demand transitions and subsequent controller perception and performance is limited. This research uses an air traffic control simulation to investigate the effect of task demand transitions, and the direction of those transitions, on workload and fatigue and one efficiency performance measure. Results indicate that a change in task demand appears to affect both workload and fatigue ratings, although not necessarily performance. In addition, participants workload and fatigue ratings in equivalent task demand periods appear to change depending on the demand period preceding the time of the current ratings. Further research is needed to enhance understanding of demand transition and workload history effects on operator experience and performance, in both air traffic control and other safety-critical domains.
workload history↗
Field Testing of LIDAR-Assisted Feedforward Control Algorithms for Improved Speed Control and Fatigue Load Reduction on a 600-kW Wind Turbine: Preprint
A severe challenge in controlling wind turbines is ensuring controller performance in the presence of a stochastic and unknown wind field, relying on the response of the turbine to generate control actions. Recent technologies such as LIDAR, allow sensing of the wind field before it reaches the rotor. In this work a field-testing campaign to test LIDAR Assisted Control (LAC) has been undertaken on a 600-kW turbine using a fixed, five-beam LIDAR system. The campaign compared the performance of a baseline controller to four LACs with progressively lower levels of feedback using 35 hours of collected data.
17 WIND ENERGY↗
Comparison of Probabilistic Forecasts for Predictive Voltage Control
This paper explores predictive cooperative voltage control in distribution systems with highly variable sources such as photovoltaics (PV). The goal is to maintain the voltage profile within the limits despite the fluctuations due to sudden changes in solar power generation. The predictive voltage control method relies on probabilistic solar power and load forecasts to select the optimum Voltage Regulator (VR) taps appropriately. VR taps are selected to minimize the risk of voltage violation. A modified version of the IEEE 123 system is used as the case study. A 100% penetration of solar power is assumed for the distribution system with profiles for solar generation and loads added to the system. Three different probabilistic forecast models (Quantile Regression (QR), Gaussian distribution and volatility forecasting using Generalized Autoregressive Conditional Heteroskedasticity (GARCH)) are explored in this study. The results for the VR taps and Voltage Deviation Index (VDI) are compared to find the most effective forecast model.
Panamtash, Hossein↗
Geometric Analysis Based Double Closed-loop Iterative Learning Control of Output PDF Shaping of Fiber Length Distribution in Refining Process
In order to improve the pulp quality and to reduce the energy consumption, the fiber length distribution (FLD) is generally employed as one of the important technological indexes in the refining process. Considering that the traditional mean and variance of fiber length are unable to adequately characterize the non-Gaussian distribution properties, this paper proposes a novel geometric analysis based double closed-loop iterative learning control (ILC) method for probability density function (PDF) shaping of output FLD in the refining process. Primarily, a RBF neural network (NN) with Gaussian-type is utilized to approximate the square root PDF in the inner loop, where the RBF basis function parameters (center and width) are tuned between any two adjacent batches by using an ILC law, and the subspace identification method can be applied to establish the state-space model of weight vector. Then, for the sake of accelerating the convergence rate of the closed-loop sysyem, a geometric analysis based ILC method is adopted in the outer loop. Lastly, both simulation and experiments demonstrate the effectiveness and practicability of the proposed approach.
42 ENGINEERING↗
Controlled Generation of Singlet Oxygen in Living Cells with Tunable Ratios of the Photochromic Switch in Metal–Organic Frameworks
Abstract Development of a photosensitizing system that can reversibly control the generation of singlet oxygen ( 1 O 2 ) is of great interest for photodynamic therapy (PDT). Recently several photosensitizer–photochromic‐switch dyads were reported as a potential means of the 1 O 2 control in PDT. However, the delivery of such a homogeneous molecular dyad as designed (e.g., optimal molar ratio) is extremely challenging in living systems. Herein we show a Zr‐MOF nanoplatform, demonstrating energy transfer‐based 1 O 2 controlled PDT. Our strategy allows for tuning the ratios between photosensitizer and the switch molecule, enabling maximum control of 1 O 2 generation. Meanwhile, the MOF provides proximal placement of the functional entities for efficient intermolecular energy transfer. As a result, the MOF nanoparticle formulation showed enhanced PDT efficacy with superior 1 O 2 control compared to that of homogeneous molecular analogues.
Park, Jihye↗
Nationwide HVAC Energy-Saving Potential Quantification for Office Buildings with Occupant-Centric Controls in Various Climates
The occupant-centric control (OCC) is receiving an increasing attention due to its ability to reduce building heating ventilation and air-conditioning (HVAC) system energy consumptions while not affecting the occupant thermal comfort. This paper aims to investigate and quantify the nationwide energy-saving potential of implementing the occupant-centric HVAC controls in typical office buildings using a whole building simulation software EnergyPlus. First, the medium office and large office from the Department of Energy (DOE) Commercial Prototype Building Models (CBPM) were enhanced to have detailed layouts and dynamic occupancy schedules. Then, a comprehensive simulation plan was created by incorporating the multiple zone-level and system-level occupant-centric building HVAC controls recommended by the updated ASHRAE Standard 90.1 – 2019 and ASHRAE Guideline 36 – 2018. Three control scenarios with different occupancy sensing methods were identified in this simulation plan. A nation-wide parametric analysis which includes two building types, three occupancy sensing scenarios, two building code versions, and 16 U.S. climate zones was carried out. The simulation results of the key control variables and HVAC energy consumption suggest that generally, both the occupancy presence sensor and occupant counting sensor could achieve energy savings for the office buildings in majority of the scenarios. However, compared with the occupancy presence sensor, which could support both the temperature setpoint reset and operational breathing zone airflow rate reset for the unoccupied zones, the occupant counting sensor only brings a marginal benefit. Besides, a higher HVAC energy-saving ratio could be achieved in the heating-dominated zone, since the energy reduction brought with the minimum outdoor airflow rate reset is stronger in the heating mode.
Pang, Zhihong↗
The QICK (Quantum Instrumentation Control Kit): Readout and control for qubits and detectors
We introduce a Xilinx RF System-on-Chip (RFSoC)-based qubit controller (called the Quantum Instrumentation Control Kit, or QICK for short), which supports the direct synthesis of control pulses with carrier frequencies of up to 6 GHz. The QICK can control multiple qubits or other quantum devices. The QICK consists of a digital board hosting an RFSoC field-programmable gate array, custom firmware, and software and an optional companion custom-designed analog front-end board. We characterize the analog performance of the system as well as its digital latency, important for quantum error correction and feedback protocols. We benchmark the controller by performing standard characterizations of a transmon qubit. We achieve an average gate fidelity of ℱ avg =99.93%. All of the schematics, firmware, and software are open-source.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗