Articles tagged with Control Systems
AQT at Berkeley Lab organized a workshop on classical control systems for quantum computing, bringing together industry leaders and researchers to share experimental control advances. The workshop highlighted the need for advanced features in classical control electronic systems to optimize quantum computer performance.
University of Missouri engineers are working on a collaborative human-robot order picking system to speed up the online delivery process. The proposed model aims to optimize key decisions in warehouse operations, allowing robots to navigate efficiently and collaborate with humans to increase efficiency.
A new study from the University of East Anglia found that employees who perceive managerial controls as restrictive and punitive may develop dysfunctional responses, including workplace deviance and deliberate ignorance. The study suggests that threatening managerial controls have different effects on skilled and non-skilled workers, w...
A new CNN framework, PE-Net, is proposed for predicting machine remaining useful life (RUL) accurately. The framework uses a novel architecture with small-sized one-dimensional convolution kernels and deep networks to learn features from input time series signals.
A recent review article summarizes the latest developments in finite-control-set model predictive control (FCS-MPC) strategies for PMSMs. FCS-MPC is a promising approach to optimize drive systems, but challenges remain, including computational complexity and parameter uncertainty.
Nagoya University scientists developed a controller with a sleep mode to procure energy only when needed, reducing the need for storage batteries and capacitors. This innovative solution enables efficient energy saving and promotes the practical application of power packet type energy Internet.
Rice undergrad Colter Decker creates programmable, air-driven circuits that can perform Boolean functions using compressed air. The system combines digital and analog components, simplifying the overall architecture and achieving new capabilities.
Bhattacharya's project uses topological abstraction to reduce complexity in robotic systems, enabling more efficient and accurate motion planning. The approach has potential applications in industries such as transportation, manufacturing, and healthcare.
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 study takes inspiration from the 'waggle dance' of honeybees to devise a way for robots to communicate effectively in situations with unreliable network communications. Researchers designed a visual communication system using on-board cameras, allowing robots to interpret gestures and convey complex information.
A new study demonstrates a machine-learning approach that can learn to control a fleet of autonomous vehicles as they approach and travel through a signalized intersection. The technique reduces fuel consumption and emissions while improving average vehicle speed, with benefits seen even when only 25% of cars use the control algorithm.
Researchers at Michigan State University have designed a learning-enabled safe controller for systems operating in uncertain environments. The new method, which combines control barrier functions and Lyapunov functions, allows the system to quickly learn uncertainties while achieving maximum safe performance.
Researchers at MIT developed a framework for robotic manipulation systems that can perform complex tasks using a two-stage learning process. This allows robots to learn abstract ideas about manipulating deformable objects, such as pizza dough, and execute skills to complete tasks.
Scientists from China have developed a bionic approach to improve wind turbine performance by combining features of a seagull's wing with an engineered flow control accessory. The combined flow control improves lift and delays stalling at high angles of attack, increasing the efficiency of wind energy turbines.
Researchers created BirdBot, a robotic leg inspired by the ostrich's anatomy, which achieves energy efficiency through a mechanical coupling of muscles and tendons. The robot leg requires fewer motors than other machines, making it suitable for large size applications.
A new internet-connected lighting system for greenhouses can optimize lighting and reduce electrical costs by up to 33% by predicting sunlight. The system uses sensors and algorithms to adjust light levels, making the most of natural sunlight and minimizing energy waste.
Researchers developed a machine learning approach enabling robots to separate, recognize, and grasp individual objects with high accuracy. The method achieved 97% success rate in real-world experiments, paving the way for industrial parts sorting and residential waste sorting applications.
A new approach uses reinforcement learning algorithm to help robotic knee mimic intact human knee in walking, achieving 100% success rate on even ground. The technology also adapts to uneven terrain and changes in walking pace, promising a more comfortable experience for prosthetic users.
The Tianwen-1 Mars rover landed successfully due to its advanced autonomous guidance, navigation and control system. The system performed reliable key event triggers and accurate state estimates to implement trajectory and attitude controls.
Researchers at UC San Diego develop precision-guided sterile insect technique (pgSIT) to control mosquito populations. The system uses CRISPR to alter genes linked to male fertility and female flight in Aedes aegypti, reducing disease transmission.
Researchers have developed a novel algorithm that improves the speed at which nodes converge on agreement regarding a single data value needed during computation. The technique is based on designing an optimized network topology that reduces communication costs while allowing for adjustable convergence rates.
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.
Drones are not the only vehicles at the forefront of automating deliveries; researchers have developed a control strategy for ships and partnered tugs to navigate environmental disturbances. The multi-layer, multi-agent control scheme increases efficiency in the shipping process while reducing human error.
Simulation models were used to estimate the COVID-19 pandemic control strategy associated with the least health losses and the most cost effectiveness in Victoria, Australia. The study aimed to find the optimal balance between health outcomes and economic costs.
A new study explores how human decision-making impacts engineered systems. Researchers found that people often overestimate their abilities and succumb to biases, leading to inefficiencies in system design.
Researchers at Oak Ridge National Laboratory have developed a hybrid inverter platform that connects local energy resources to the utility power grid, enabling autonomous, distributed energy systems. The platform can interact with various control systems and support real-time monitoring for better system stability.
Texas A&M University researchers aim to develop a smart ventilation control system to minimize the risk of COVID-19 infection in public buildings. The project seeks to investigate a smart ventilation control system that can operate in both normal and emergency modes, utilizing factors such as outdoor air dilution and humidity levels.
A self-learning heating control system has been developed by Empa researchers, allowing for energy savings of up to 25% in residential buildings. The system uses machine learning and weather forecasts to optimize temperature settings, providing greater comfort while reducing energy consumption.
A Wayne State University research team will develop algorithms to detect and prevent cyberattacks on chemical process control systems, enhancing production efficiency and safety. The three-year project aims to create stronger safeguards against automation system attacks.
A team of researchers is creating an advanced autopilot system that can autonomously evaluate unforeseen circumstances and land a plane safely. The system will combine image processing, on-board computers, and sensor redundancy to defend against catastrophic failures.
Researchers at the University of Seville developed a predictive method to quantify energy and economic savings from using smart lighting control systems. The study found that these systems can generate significant energy savings, especially when paired with efficient LED lighting.
Researchers developed a new foldable drone that can squeeze itself through narrow passages and navigate tight spaces. The drone's mobile arms can fold around the main frame, allowing it to maintain stable flight while adapting to different configurations.
Researchers at UConn have created a tiny neuro-controller that can precisely control the movement of cyborg cockroaches. The system, which includes an inertial measurement unit and real-time feedback, enables operators to steer the insect in desired directions.
A new simulator, GRFICS, allows users to play the roles of attackers and defenders in a virtual chemical processing plant. The system helps operators learn to detect attacks and respond appropriately, reducing vulnerabilities in industrial control systems.
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 child-like android named 'ibuki' was developed to facilitate human-robot interaction. The robot's conversation control system allows it to regulate speech, motion, gaze, and emotion based on its intention, increasing perceived human-likeness. This technology enables more natural conversations and social interactions.
A team of researchers has developed a minimal logic system to bridge the gap between mathematical proofs, algorithms, and real-world outcomes in control systems. The work, published in IEEE/CAA Journal of Automatica Sinica, aims to improve the realism of theoretical mathematics by focusing on computational certainty.
A new smart grid system has been developed to reduce inter-area oscillations on the western power grid, allowing for more power to be transmitted while maintaining stability. The system uses real-time data from sensors placed throughout the grid to counteract oscillations, enabling utilities to save costs and improve efficiency.
Sandia engineers have designed a control system that doubles the power absorbed by wave energy converters, making electricity produced from wave energy less expensive. The team applied robotics and aerospace engineering design principles to refine how a wave energy converter moves and responds in the ocean.
I_Systems' advanced control system Leaf enables companies to forecast consumption variations and optimize air flow and fuel intake, leading to cost savings. The technology has been successfully implemented by various customers in 25 industries, including Coca-Cola and Suzano Papel e Celulose.
The UPV/EHU's Advanced Control Group has successfully developed a sliding mode controller to maintain maximum power point of solar panels despite changes in irradiation and load. This control system offers improved efficiency compared to traditional algorithms, which cause oscillating working points and diminish efficiency.
Researchers at Georgia Tech have developed a new form of ransomware that can take over control of simulated water treatment plants, highlighting vulnerabilities in industrial control systems. The attack demonstrates the potential for attackers to compromise programmable logic controllers (PLCs) and hold critical systems hostage.
The proposed scheme considers vehicle shape and road width to minimize collisions and optimize path tracking. The model predictive control method effectively tracks the desired lateral position of road centerline, avoiding collisions and ensuring low energy consumption.
A new simplified mass-spring-bar model is presented for the semi-pelagic trawl system, enabling trajectory tracking and control of the trawl net and two otter boards. The proposed hybrid control approach combines stability analysis with S-plane control to ensure effective motion control.
Researchers developed a new setpoint-tracking strategy using fractional calculus to improve the response time and stability of automated systems. The approach outperformed classical integer-order filters in tracking complex paths, offering potential benefits for applications like robotics, self-driving cars, and medical devices.
Scientists propose a new control system design using Fractional-Order Generalized Principle of Self-Support (FOGPSS), disregarding traditional cause-and-effect definitions. The model uses fractional order calculus to describe potential outcomes over time, allowing for robustness and adaptability in systems with long-term memory.
Researchers at UNIST are developing a new form of futuristic transportation using the Hyperloop technology, which could reduce travel times from Seoul to Busan to just 16 minutes. The team aims to overcome challenges such as air resistance and friction by using magnetic levitation and innovative power supply systems.
Researchers at Georgia Institute of Technology have developed a device fingerprinting technique to identify legitimate signals in electrical grid control networks. The approach uses unique physical properties of devices to differentiate between genuine and spoofed signals, improving the security of critical infrastructure networks.
A Kansas State University researcher has received a $446,000 NSF CAREER award to develop robust verification of cyber-physical systems, enabling high-confidence systems in automotive and aerospace applications. The project aims to bridge a gap in existing methodologies for cyber-physical system analysis.
This study models and verifies the behavior of Chinese Train Control System Level 3 (CTCS-3) using the Architecture Analysis & Design Language (AADL). The authors use the Behavior Language for Embedded Systems with Software (BLESS) and Hybrid Annex (HA) sublanguages to capture discrete and continuous behaviors, respectively. They verif...
A control system that incorporates electrical signals generated during muscle contractions and gait information resulted in improved real-time control of a powered prosthetic leg for different modes of walking. This system reduced classification error rates by an average of 41% compared to mechanical sensor data alone.
A Chinese research team proposes a novel approach to verify the correctness of high-speed train control systems, combining simulation and formal verification. The method models the system using Simulink/Stateflow and then transforms it into a formal Hybrid CSP model for verification, advancing the state-of-the-art in verifying train co...
Researchers at the University of Illinois have developed an adaptive control technology that can override failures and maintain safe handling in aircraft. The L1 system has been tested on a manned aircraft and shown consistent performance across varying flight conditions, making it a promising solution for improving air travel safety.
Researchers are developing a biologically plausible model of the whole system to predict outcomes of future experiments and provide more information about the brain's ability to learn new motor movements. The goal is to understand how people execute, control and learn movements to lead to new treatments for Huntington's disease.
New research will focus on understanding and mitigating threats to industrial control systems, including manufacturing plants, power stations, and the rail network. The project aims to provide effective interventions to counter cyber risks and improve risk communication.
The system eliminates vibrations caused by human muscle co-contraction, allowing the robot to move safely and efficiently. By modeling human operators in this way, robots can actively adjust to changes in movement, improving performance and safety in manufacturing plants.
The University of Washington is partnering with OceanGate to develop a five-person deep-sea manned submarine that can reach depths of over 9,842 feet. The Cyclops submarine features a carbon-fiber hull and advanced control systems, allowing for increased safety and efficiency in ocean research and exploration.
Researchers from North Carolina State University have developed a software algorithm that can detect compromised agents in distributed network control systems, allowing for isolation and protection of the entire system. This provides resilience and security advantages over traditional centralized systems.
Researchers at Ohio State University developed a four-wheel independently actuated (FIWA) electric car with exceptional traction and motion control, keeping its four wheels and four motors on the road. The system enables enhanced maneuverability and control without emissions.
The Idaho National Laboratory has demonstrated a suite of cybersecurity tools that provides situational awareness of networks and control systems. The Sophia software tool passively observes network communications, providing real-time and historical records of those communications.