Official implementation of "Reinforcement Learning-Enhanced Model Predictive Control with Meta-Learning for Online Compensation of Dynamic Model Errors".

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

1 Department of Electrical Engineering, College of Engineering, University of Baghdad, Baghdad, Iraq 2 Department of Electrical Engineering, College of Engineering, University of Wasit, Wasit, Iraq ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

Cancer, Alzheimer’s, and other diseases follow a pathway in the human body. It starts at the molecular and cellular levels, and through a series of complex interactions can lead to the development and ...

Large language models are typically refined after pretraining using either supervised fine-tuning (SFT) or reinforcement fine-tuning (RFT), each with distinct strengths and limitations. SFT is ...

Abstract: Direct Current (DC) motors are extensively used in industrial applications for their versatility in speed control and adaptability. This paper introduces a Reinforcement Learning (RL)-based ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this research work authors have experimentally validated a blend of Machine ...

Abstract: The PID control algorithm is the most used industrial control method owing to its simplicity and ease of use. However, tuning PID parameters is not trivial and many methods have been ...