A new AI model learns to "think" longer on hard problems, achieving more robust reasoning and better generalization to novel, unseen tasks.

This paper reports an effective quintic polynomial-based trajectory planning approach and a robust tube-based model predictive control (RTMPC) method for an underactuated tractor-trailer vehicle ...

DL-MPC (deep learning model predictive control) is a software toolkit developed based on the Python and TensorFlow frameworks, designed to enhance the performance of traditional Model Predictive ...

Learn how to build a predictive machine learning model for manufacturing. This comprehensive guide explores its benefits, applications, and development process.

Differentiable Robust Model Predictive Control. (arXiv:2308.08426v1 [math.OC]) https://ift.tt/VeB97rb Deterministic model predictive control (MPC), while powerful, is often insufficient for ...

This study attempts to offer an alternative to the problem of implementing model predictive controllers (MPC) in conditions where the timescale multiplicity of the process model is not accounted for ...

In this paper, we integrate the blueonline-updating Gaussian Process (GP) models into the Model Predictive Control (MPC) design of nonlinear systems with time-varying dynamics to obtain a more ...

The predictive controller is realized by regressing the predictive model using online process data and the incremental broad learning algorithm. The proposed model predictive control (MPC) approach ...