✦ LIBER ✦

Extended robust model predictive control

✍ Scribed by D. Odloak

Publisher: American Institute of Chemical Engineers
Year: 2004
Tongue: English
Weight: 176 KB
Volume: 50
Category: Article
ISSN: 0001-1541
DOI: 10.1002/aic.10175

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Extended robust model predictive control of integrating systems

✍ Alejandro H. González; Jacinto L. Marchetti; Darci Odloak 📂 Article 📅 2007 🏛 American Institute of Chemical Engineers 🌐 English ⚖ 291 KB 👁 2 views

Robust model predictive control for unce

Robust model predictive control for uncertain step response

✍ Jianping Zou; Yash P. Gupta 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 366 KB 👁 2 views

The design of robust model predictive control for handling bounded uncertainties in step response of unconstrained MIMO processes is considered. The control law is obtained by minimizing an upper bound of the objective function and it consists of an optimal state feedback gain and a robust state obs

Robust nonlinear model predictive contro

Robust nonlinear model predictive control of batch processes

✍ Zoltan K. Nagy; Richard D. Braatz 📂 Article 📅 2003 🏛 American Institute of Chemical Engineers 🌐 English ⚖ 261 KB 👁 2 views

Robust steady-state target calculation f

Robust steady-state target calculation for model predictive control

✍ Dean E. Kassmann; Thomas A. Badgwell; Robert B. Hawkins 📂 Article 📅 2000 🏛 American Institute of Chemical Engineers 🌐 English ⚖ 276 KB 👁 2 views

## Abstract In practice, model predictive control (MPC) algorithms are typically embedded within a multilevel hierarchy of control functions. The MPC algorithm itself is usually implemented in two pieces: a steady‐state target calculation followed by a dynamic optimization. A new formulation of the

Robust model predictive control and faul

Robust model predictive control and fault handling of batch processes

✍ Siam Aumi; Prashant Mhaskar 📂 Article 📅 2010 🏛 American Institute of Chemical Engineers 🌐 English ⚖ 441 KB 👁 2 views

This work considers the control of batch processes subject to input constraints and model uncertainty with the objective of achieving a desired product quality. First, a computationally efficient nonlinear robust Model Predictive Control (MPC) is designed. The robust MPC scheme uses robust reverse-t

Chance-constrained model predictive cont

Chance-constrained model predictive control

✍ Alexander T. Schwarm; Michael Nikolaou 📂 Article 📅 1999 🏛 American Institute of Chemical Engineers 🌐 English ⚖ 226 KB 👁 3 views