Learn how the Neural Network Predictive Controller uses a neural network model of a nonlinear plant to predict future plant performance. Learn the design of a NARMA-L2 Neural Controller. …

Learn how the Neural Network Predictive Controller uses a neural network model of a nonlinear plant to predict future plant performance.

There are three well-known typical neural network controllers: Model Predictive Control, Feedback Linearization Control, and Model Reference Control. There are two steps involved when using …

May 24, 2022 · Model predictive control (MPC) has attracted significant research interest as it is one of the major achievements in the development of advanced multivariate process control …

At its heart, an MPC controller uses a model of the system to predict its expected evolution in response to its controlled and uncontrolled inputs. Specifically, the system is assumed to be …

Find the control law directly from the data using RL techniques. Motivation: Eliminates the need of plant modeling and the online optimization. Approximate the MPC control law. Replace the …

Nov 1, 2022 · This work proposed a novel neural-network-based model predictive control algorithm so that a nonlinear multi-agent system reaches consensus with stochastic switching …

We propose in this paper the use of a finite-horizon oracle controller with perfect knowledge of all system parameters as a reference for optimal control actions. First, this allows us to...

Part of the book series: Studies in Computational Intelligence ( (SCI,volume 252)) This work is concerned with Model Predictive Control (MPC) algorithms in which neural models are used …

Macroscopic traffic flow forms show heavily similarity between days, so this paper uses past datas to train a neural network for fitting the MFD system. This paper presents a framework for...