Scientific Research Publishing

Hybrid Deep Reinforcement Learning and Model Predictive Control for Microgrids ()

The current microgrids are experiencing growing difficulties in voltage stability and operational capacity, particularly with constant power loads (CPLs), leading to negative impedance behavior and ...
Nature

Non-linear model predictive control for variable speed hydropower

Inverter Based Resources (IBR) are gaining more popularity in modern power systems, leading to decrease in grid inertia. Hydropower Plants with rotating synchronous machines have been excellent source ...
webtv.un.org

UN High-Level Meeting on the Prevention and Control of Noncommunicable Diseases and the Promotion of Mental Health

The UN High-Level Meeting on the Prevention of Noncommunicable Diseases and Mental Health (NCDs) in 2025 is a key moment for Heads of State and Government, civil society, academia, philanthropies, and ...
IEEE

Approximate Nonlinear Model Predictive Control With Safety-Augmented Neural Networks

Model predictive control (MPC) achieves stability and constraint satisfaction for general nonlinear systems but requires computationally expensive online optimization. This brief studies ...
GitHub

Nonlinear model predictive control(NMPC) with Extended State Observer(ESO) for robust quadrotor control, built on PX4 autopilot framework.

src/ ├─ px4ctrl/ # ESO-NMPC controller core ├─ sim_rc/ # Remote control simulator │ └─ sim_rc_node # Gazebo RC simulation node ├─ utils/ # Dependency packages │ ├─ cmake_utils/ # CMake configuration ...
IEEE

Nonlinear Model Predictive Control for Internet of Things Using Particle Swarm Optimization and Cloud Computing

Abstract: This paper proposes a novel model predictive control design for Internet of Things (IoT) applications by using the generalized opposition-based learning particle swarm optimization algorithm ...
C&EN

Efficient Model Predictive Control Implementation via Machine Learning: An Algorithm Selection and Configuration Approach

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...
Nature

Digital twin syncing for autonomous surface vessels using reinforcement learning and nonlinear model predictive control

Current control systems for autonomous surface vessels (ASVs) often disregard model uncertainties and the need to adapt dynamically to varying model parameters. This limitation hinders their ability ...