A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

Abstract: This study presents a comparative study of an interleaved boost converter using various control methods, such as Model Predictive Control (MPC) and traditional PID control. Based on settling ...

Artificial intelligence (AI) is transforming the energy sector, helping power plant operators optimize efficiency, reduce emissions, and prevent costly equipment failures. By analyzing vast amounts of ...

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 ...

Abstract: This paper presents the design of the Practical Nonlinear Model Predictive Control (PNMPC) for liquid level control. In this research, the developed nonlinear control algorithm (PNMPC) has ...

The TensorDL-MPC toolbox is a Python-based software developed using the TensorFlow framework. It leverages deep learning techniques to enhance the performance of traditional Model Predictive Control ...

Key Laboratory of Green Process and Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China School of Chemical Engineering, University of Chinese Academy of ...

Add a description, image, and links to the nonlinear-model-predictive-control topic page so that developers can more easily learn about it.