W Tang, P Daoutidis - 2022 American Control Conference …, 2022 - ieeexplore.ieee.org
Process systems are characterized by nonlinearity, uncertainty, large scales, and also the need of pursuing both safety and economic optimality in operations. As a result they are …
A supervised learning framework is proposed to approximate a model predictive controller (MPC) with reduced computational complexity and guarantees on stability and constraint …
A Alessio, A Bemporad - Nonlinear Model Predictive Control: Towards …, 2009 - Springer
Explicit model predictive control (MPC) addresses the problem of removing one of the main drawbacks of MPC, namely the need to solve a mathematical program on line to compute …
In this paper we study the effect of false data injection attacks on state estimation carried over a sensor network monitoring a discrete-time linear time-invariant Gaussian system. The …
S Richter, CN Jones, M Morari - IEEE Transactions on …, 2011 - ieeexplore.ieee.org
This paper proposes to use Nesterov's fast gradient method for the solution of linear quadratic model predictive control (MPC) problems with input constraints. The main focus is …
This paper describes nonlinear methods in model building, dynamic data reconciliation, and dynamic optimization that are inspired by researchers and motivated by industrial …
In this paper relations between model predictive control and reinforcement learning are studied for discrete-time linear time-invariant systems with state and input constraints and a …
M Ławryńczuk - A Neural Network Approach, Studies in Systems …, 2014 - Springer
In the Proportional-Integral-Derivative (PID) controllers the control signal is a linear function of: the current control error (the proportional part), the past errors (the integral part) and the …
B Ponton, M Khadiv, A Meduri… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This article investigates the problem of efficient computation of physically consistent multicontact behaviors. Recent work showed that under mild assumptions, the problem …