Articles tagged with Optimal Control
The study reveals geographic clusters of high and low screening for breast, cervical, and colorectal cancers in the US Northeast and Southwest. Future studies could examine county-level healthcare access to optimize cancer screening practices.
The study reveals that balance is key in engineering cells to produce more chemicals without antibiotics or complex methods. The team designed genetic circuits using negative feedback systems to optimize cell factories, increasing function by threefold and cumulative chemical production over time.
Researchers from the Institute of Industrial Science, The University of Tokyo, have developed a mathematical theory that can be used to design optimization strategies for dynamical networks, such as those comprising living organisms. They found that tools from information theory provided a way to simplify nonlinear optimization problem...
A team of researchers has designed a servicing plan for future space observatories, inspired by current missions like the James Webb Space Telescope and the European Space Agency's Gaia. The plan aims to address the enormous challenges of implementing serviceability in modern space telescopes, including distance and delicate structures.
A team of researchers at the University of Illinois has developed a multimode propulsion system that integrates both chemical high-thrust mode and electric low-thrust mode, resulting in reduced fuel consumption and increased flexibility. The system uses the same propellant for both modes, saving mass and volume.
Researchers at the Gwangju Institute of Science and Technology (GIST) have developed an innovative robotic rehabilitation system called SPINDLE to enhance the strength and dexterity of individuals with tremors. The study revealed significant benefits, including improved motor control, coordination, and neuroplasticity.
Researchers developed novel optimal and robust-optimal controllers for the FDS model, achieving six-fold reduction in settling time and improved stability. The robust-optimal controller performed better than the optimal controller in simulations with noise, demonstrating its adaptability.
Studies at the University of Gothenburg found a clear shift in arterial disease risks in diabetes, with decreases in central organ diseases like heart attack and stroke, but increases in peripheral vessel complications. Closer monitoring of long-term blood sugar levels can reduce peripheral arterial disease risk by 30-50%.
A new technique has been developed to cool quantum simulators, allowing for more stable experiments and better insights into quantum effects. By splitting a Bose-Einstein condensate in a specific way, researchers can reduce temperature fluctuations and enhance the performance of quantum simulators.
A team of researchers developed a time-optimal control method for autonomous ships, optimizing maneuvering performance in dynamic sea conditions. The new control system accounts for various forces affecting ship movement and can improve efficiency and safety, reducing shipping costs and carbon emissions.
A team at Zhejiang University has developed a self-driving cloaked unmanned drone with an intelligent aeroamphibious invisibility cloak, capable of manipulating electromagnetic scattering in real-time across dynamic environments. The cloak integrates perception, decision-making, and execution functionalities using spatiotemporal modula...
The project aims to assess the operational resilience of microgrids on DoD installations and ships, using new operational resilience indexes developed by Lehigh University researcher Javad Khazaei. The team will develop a dashboard to monitor resilience indexes in real-time, providing recommendations for improving the systems.
A new research paper challenges the idea that unlimited trials are needed to learn safe actions in unfamiliar environments. The team presents a fresh approach that ensures learning safe actions with complete confidence while managing tradeoffs between optimality and exposure to unsafe events.
A new strategy balances disease control with resistance management by balancing resistance to both fungicides until it increases enough to fail. The approach is robust to variations in parameters and could influence policy recommendations.
Researchers have proved that a long-standing game theory dilemma does not exist in the wall pursuit game, introducing a new method of analysis that proves there is always a deterministic solution. This discovery opens doors to resolving other similar challenges and enables better reasoning about autonomous systems.
Researchers propose an alternative redistricting procedure that takes input from two major political parties and results in quantifiably fairer district maps. The bisection protocol, inspired by the
The study developed an extended deep Q-network (EDQN)-incorporated context-based meta-RL model that can autonomously detect traffic states, classify regimes, and assign signal phases. The model outperformed existing algorithms in simulation experiments and showed adaptability to new tasks without adjusting parameters.
A large stroke trial found that intensive blood pressure lowering after clot removal compromises the return of blood flow to the affected area, leading to more brain tissue deterioration and major disability. The study suggests that this increasingly common treatment strategy should be avoided in clinical practice.
A new method combines Centroidal Voronoi tessellation (CVT) and Model Predictive Control (MPC) to optimize microsatellite swarm trajectories, ensuring collision avoidance while minimizing fuel consumption. Numerical simulations validate the effectiveness of this macro-micro trajectory planning approach.
A new study from Kaiser Permanente found that pregnant women with gestational diabetes who achieve rapid glucose control have better birth outcomes. The research analyzed data from over 26,000 patients and identified four trajectories of glucose control, with those starting out with optimal levels and maintaining it having the best res...
Researchers at MIT develop a new flow model that optimizes individual turbine control to maximize wind farm energy production. The algorithm increases energy output by up to 32% in real-world experiments, with potential gains of over $1 billion per year.
A new review paper assesses recent progress in controlling quantum systems and applies it to emerging technologies, highlighting the need for a unified theoretical framework. The authors identify roadblocks that must be overcome to manifest a future quantum technological landscape.
A cluster-randomised trial in Singapore showed a low-cost, multi-pronged intervention improved BP control, reduced cardiovascular risk and increased use of antihypertensive medications. The intervention could cut hypertension-linked morbidity and mortality globally with rapid scalability.
Researchers developed a machine learning method to create controls that balance building energy cost, comfort, and efficiency. The system can compute solutions at a fast pace, reducing the need for complex model predictive controllers.
Researchers developed a software-based smoke dispersal simulation model to study prehistoric archaeology. They found that early humans placed their hearth at the optimal location in the cave, enabling maximum utilization of fire while minimizing smoke exposure. The study identified a 25sqm area as ideal for locating the hearth.
Researchers have created a new, simpler way to fabricate SERS nanostructures with superior stability and performance at low cost. By using a heat-resistant polymer called polyimide (PI), they can produce nanosurfaces with nanopillars that enhance signal intensity for efficient chemical detection. The new fabrication method has the pote...
QUT researchers developed a new mathematical model to enable faster solutions for complicated problems in agriculture, ecology and medicine. The method improves how to determine the 'best' intervention strategies, balancing benefits and side effects, and can be applied to farming practices and chemotherapy.
A team of researchers has created a new algorithm that determines the most efficient route for robots to navigate complex spaces. The RBF-Galerkin method combines two existing approaches to find the optimal solution, surpassing other methods in terms of cost and time efficiency.
Researchers developed a modular robot that autonomously adapts to its environment, achieving optimal behavior without a central controller. The robot learned to navigate and maintain behavior even with damage, paving the way for miniaturized robotic materials for various applications.
The research team applied filter functions and optimal quantum control theories to detect known signals from background noise in quantum bit (qubit) sensors. They obtained analytical insight into the optimal control protocol when background noise is white, similar to classical matched filtering scheme.
A researcher from Ural Federal University developed a new approach to solving optimal control problems for groups of objects. By applying the concept of dynamic stability, he created partial differential equations that predict the behavior of multiple agents in conflict situations.
Researchers at MIT have created a system called RoboGrammar that optimizes the shape of robots for traversing different terrain types. The system uses a graph grammar inspired by arthropods to generate hundreds of thousands of potential robot structures, which are then evaluated using a neural network algorithm.
The U.S. Army has developed a reinforcement learning approach that enables swarms of unmanned aerial and ground vehicles to accomplish various missions while minimizing performance uncertainty. This allows for efficient execution of time-consuming or dangerous tasks, enhancing warfighters' tactical situational awareness.
The American Thoracic Society's new guideline recommends varenicline as the optimal controller medication for clinicians to use initially in treating tobacco dependence. Introducing varenicline before a patient expresses willingness to quit results in an additional 308 patients achieving abstinence.
Researchers propose STyLuS*, a new approach to solving complex robot control problems, by growing 'trees' in the search space to find optimal solutions. This method reduces memory requirements and processing power needed for large-scale robotic tasks.
A new study published in Frontiers in Psychology found that competitive esports athletes cope with stress similarly to high-performing sports athletes. Esports players with higher ranks tend to have higher levels of mental toughness, which can be beneficial for optimal performance.
A mathematical model has been developed to predict how invasive species spread in rivers and how to control their movement using optimal water flow rates. The study, published in Mathematics, uses a partial differential equation model to illustrate how adjusting the water flow rate can prevent invasive populations from expanding upstream.
Researchers develop new methods to optimize vibration shock protection systems, considering uncertainty and multicriteria tasks. The approach leads to a significant advance in the theory and practice of vibration shock protection.
Researchers designed a novel robotic jellyfish capable of 3D motion, leveraging reinforcement learning-based control to achieve high-order structure flexibility and yaw maneuverability. The system, inspired by Aurelia aurita, has great implications for bioinspired design of jet propulsion systems with agility.
Researchers at the Institut Pasteur successfully reprogrammed immune cells from individuals who naturally control HIV infection, granting them enhanced antiviral potency. This breakthrough could lead to novel treatments and potential cure options for those living with HIV, as previously described in a study published in Nature Metabolism.
Researchers have developed a new flight strategy to land heavier vehicles on Mars by eliminating parachutes and using larger rocket engines. The approach optimizes the lift vector to minimize propellant usage, enabling vehicles to carry more payload while reducing costs.
Russian scientists have solved multicriteria problems of dynamic object control under uncertainty of external effects, enhancing the efficiency of controlling rotor motion in active magnetic bearings. The new methods utilize feedback control laws to minimize disturbance quenching levels and provide optimal solutions.
A mathematical model proposes a threshold strategy for governments to counterbalance the costs of reducing public debt. The optimal threshold is endogenously determined based on inflation levels.
Researchers at Lobachevsky University and University of Calabria propose new visual techniques to compare nature-inspired and deterministic global optimization algorithms. Their experiments show that both classes of methods are competitive, with performance depending on computational budget.
The special focus on formation control of unmanned systems presents recent significant achievements in theoretical design and applications. Key findings include the use of consensus-based approaches for simultaneous attack problems and hybrid particle swarm optimization for multi-UAV formation reconfiguration.
Researchers have developed a new algorithm to optimize battery power consumption in smart home systems. The system learns to adapt to real-time electricity rates and minimizes grid power needed while extending battery life. Future work will investigate avoiding damage caused by frequent charging and discharging modes.
Researchers developed a method to compute optimal traffic light settings for urban intersections by applying traffic flow conservation laws on networks. The approach uses partial outer convexification, splitting the problem into two stages: nonlinear dynamic optimization and linear mixed-integer programming.
A team of researchers from the Polytechnic University of Bari proposes a new control scheme that improves dynamic performance and disturbance rejection. They also introduce an improved pre-filter to assist the system in maintaining attention on relevant data, enabling quicker integration and acceptance.
A University of Michigan robot, MARLO, can now walk down steep slopes and uneven ground using a novel feedback control algorithm. The algorithm's potential benefits extend to powered prosthetic legs and other two-legged robots.
Researchers at PPPL designed and tested a 'liquid lithium limiter' that circulated protective liquid metal within the walls of China's EAST tokamak, keeping plasma from cooling down and halting fusion reactions. The system improved tokamak performance by reducing impurities and maintaining optimal plasma conditions.
NREL's projects focus on advancing transformational technologies for more efficient, renewable, and resilient energy systems. The lab is developing novel solar cell manufacturing processes and extreme-scale wind turbines to expand offshore wind energy access.
The study proposes adaptive control techniques to manage pests, which can help reduce crop losses due to pest control. The approach tolerates uncertainty in pest dynamics, making it suitable for developing better models or adopting design approaches that tolerate the likely level of uncertainty.
Researchers at the University of Pittsburgh are working on developing a hybrid walking exoskeleton that combines functional electrical stimulation (FES) and powered frames. The goal is to create a more efficient and effective system for paraplegics to walk, with potential applications in rehabilitation science and consumer technology.
A new learning method for energy optimization of plug-in hybrid electric buses uses stochastic Markov models to minimize fuel and electric consumption costs. The approach avoids the curse of dimensionality problem by approximating the cost function without discretization, reducing computational complexity.
A team developed a graphical representation of nuclear spin matrices for coupled spins in arbitrary quantum states, enabling better control and utilization of quantum phenomena. The 'SpinDrops' app provides intuitive access to the fascinating world of quantum control theory.
A pair of mathematicians from France propose a system of ordinary differential equations to optimize running strategies. The model uses physiological parameters and energy conservation principles, allowing for the prediction of ideal race performances.
The article emphasizes the need for sustainable integrated vector management strategies to address insecticide resistance and control malaria. Researchers argue that such approaches, inspired by agricultural practices, can provide more effective and durable pest management.
Wayne State University researchers are building an experimental wireless networking infrastructure with a $300,000 NSF grant to explore applications such as smart grids, transportation, and healthcare. The network will utilize WiMAX technology and be connected to the NSF's Global Environment for Network Innovations backbone.
Researchers have developed joint source-channel encoding/decoding (JSCC/JSCD) techniques to overcome the limitations of Shannon's separation theory in practical applications. The new schemes utilize variable-length coding and symbol-level trellis decoding to achieve better performance than existing methods.
A recent study published in PLoS Computational Biology reveals that the human brain plans movements by integrating biological and environmental constraints. The researchers discovered a mathematical principle that predicts short periods of muscle inactivation during arm movements, which is a novelty in motor control studies.