Latest Articles for Control Systems

Investigating how reinforcement learning can improve tokamak magnetic control.

New algorithms improve control for complex systems like hypersonic vehicles.

A new approach to optimize quantum gates while respecting amplitude constraints.

A method for decision-making with incomplete information focusing on cautious optimization.

This article discusses optimizing control systems while managing associated risks.

Research introduces control strategies for stabilizing quantum entanglement in qubit systems.

Research advances fault-tolerant controllers for reliable OPO performance in quantum optics.

New strategies improve control of complex systems without intrusive measures.

New methods enhance control strategies for uncertain engineering systems.

Combining neural networks with traditional methods improves airbrake safety and performance.

Exploring new methods for identifying non-causal dynamic systems using kernel-based techniques.

Researchers tackle complex control systems for free-floating robots using advanced frameworks.

A look into the role of zeros in linear systems and their implications.

Exploring control methods to improve robot stability in dynamic environments.

A new method stabilizes wave equations affected by time delays in control systems.

New methods improve the control of complex nonlinear systems in engineering.

This article highlights concerns about the robustness of neural network controllers.

A look into dephasing and control in two-qubit systems for quantum computing.

A framework to boost performance in continuous-time reinforcement learning systems.

New frameworks improve drone performance using learning and adaptive control methods.

A new technique improves real-time control of energy systems using reinforcement learning.

A look at how these systems guide agent interactions.

GF-RLS offers improved adaptability and stability in parameter estimation methods.

Learn techniques to simplify complex passive systems while maintaining key properties.

Improving efficiency and product yield through optimal control in chemical reactors.

MPCGPU speeds up control in robotics using GPUs for enhanced precision.

This article examines stability conditions in impulsive systems with interacting components.

Balancing accuracy and efficiency in modeling dynamic systems for wind energy.

This research presents a novel algorithm for estimating parameters in hybrid systems.

A new framework for assessing the stability of differential-algebraic systems under uncertainty.

A method to improve decision-making speed in Model Predictive Control systems.

New control methods improve robot adaptability to environment changes.

Innovative data-driven approaches improve online control of systems with unknown dynamics.

A novel control method enhances coordination of underwater vehicles for various tasks.

Exploring how deadbeat coupling facilitates synchronization in various systems.

An overview of switched linear systems and their significance in control design.

Learn how FMPC improves control of nonlinear systems.

Lipschitz-Constrained Neural Networks enhance prediction accuracy in complex systems.

Exploring multi-learning and its impact on reinforcement learning stability and performance.

Researchers find ways to improve the balancing of underactuated robots while they move.