Cloud computing has revolutionized the provisioning of computing resources, offering
scalable, flexible, and on-demand services to meet the diverse requirements of modern …

This paper presents a novel model-free switching and control method for three-level neutral
point clamped (NPC) converter using deep reinforcement learning (DRL). Our approach …

Artificial Intelligence and Machine Learning-based intelligent control algorithms are
replacing traditional control algorithms due to their adopting and self-learning capabilities …

This work is an exploratory research concerned with determining in what way reinforcement
learning can be used to predict optimal PID parameters for a robot designed for apple …

Quadrotor drone control is a popular domain for control research and reinforcement learning
applications. Existing control applications for quadrotor drones can be leveraged to improve …

In this paper, an adaptive PI controller based on deep Q network (DQN) is proposed, which
improves the speed control performance of the permanent magnet synchronous motor …

Current methods in reinforcement learning typically strive to develop control strategies with
no prior controller structure or domain knowledge. These approaches are favorable as they …

Ankle injuries are quite prevalent and are one of the leading factors that might prevent a
person from engaging in daily activities. These injuries may result from running, falling, a …

Çalışmamızda Q-öğrenme tabanlı adaptif PID kontrolörün gerçek zamanlı bir sistemdeki
performansı incelenmiştir. Gerçek zamanlı sistem olarak DA makine hız kontrolü sistemi …