The first stage of model predictive control is to train a neural network to represent the forward dynamics of the plant. The prediction error between the plant ...

Mar 15, 2022 · We present Real-time Neural MPC, a framework to efficiently integrate large, complex neural network architectures as dynamics models within a model-predictive ...

This paper describes three nonlinear Model Predictive Control (MPC) algorithms for neural Wiener models. In all algorithms the model or the output trajectory is ...

Aug 13, 2022 · An overview of the recent developments of time-series neural network modeling is presented along with its use in model predictive control ...

In this article, we present the application of a neural-network-based model predictive control scheme to control pH in a laboratory-scale neutralization ...

A neural network controller is applied to the optimal model predictive control of constrained nonlinear systems. The control law is represented by a neural ...

Oct 12, 2023 · This work presents the experimental implementation of a deep neural network (DNN) based nonlinear MPC for Homogeneous Charge Compression Ignition (HCCI) ...

This work is concerned with Model Predictive Control (MPC) algorithms in which neural models are used on-line. Model structure selection, training and ...

Aug 13, 2024 · This research introduces a new technique to control constrained nonlinear systems, named Lyapunov-based neural network model predictive ...

Model Predictive Control (MPC), a control algorithm which uses an optimizer to solve for the optimal control moves over a future.