Here is how to explore real-time controllers and create better robots. Robotics is a resource-intensive field, especially ...

Glucopilot dynamic dosing algorithm was associated with improved glycemic control especially among subgroups with ...

Researchers have used the jellyfish search algorithm to optimize solar PV distributed generation placement and sizing. They have tested the algorithm on an IEEE 33-bus system, with one, two, or three ...

Through industry–academia collaboration, a joint research team developed an Integrated Network-Computing Load Balancing ("INCL Balancing") simulator optimized for next-generation 6G services. This is ...

This paper introduces a new approach for controlling electric steering systems. This new control algorithm combines backstepping (BS) and PID (Proportional Integral Derivative) techniques. The output ...

The problems were solved using DIDO©, a MATLAB® toolbox for solving optimal control problems. 1 DIDO implements a guess-free, 2 fast spectral algorithm based on pseudospectral optimal control theory.

Model Predictive Control (MPC) is a widely used optimization-based control strategy for constrained systems. MPC relies on the repeated online solution of an optimal control problem, which determines ...

Breaking down the complexities of control algorithm trade-offs can help your team grasp the concept better. To make it easier: Use everyday analogies: Compare algorithm choices to familiar ...

The main contribution of this article is to leverage the superior qualities of the PI (2DoF) algorithm for enhanced performance, stability, and robustness of the WECS under uncertainties. Finally, the ...

This paper introduces four co-simulation platforms for testing deep reinforcement learning (DRL)-based control solutions in power systems. The first one is to connect the off-the-shelf Matlab DRL ...