Autocovariance-based plant-model mismatch estimation for linear model predictive control

Data-Driven Plant-Model Mismatch Quantification in Model Predictive Control

In this paper, we present a novel data-driven approach for estimating plant-model mismatch for linear MIMO systems operating under constrained MPC. We begin with analyzing the closed-loop plant data; under the assumption that changes in the active set of constraints of the controller are due to (low frequency) setpoint changes, we separate the data into a finite number of fixed active set (FAS)...

Model Based Predictive Control for Linear Systems

Model-based Predictive Control of a Pre-denitrification Plant: a Linear State-space Model Approach

1 Author to whom all correspondence should be addressed. Abstract: This paper focuses on the design of a model-based predictive control (MPC or MBPC) technique to regulate the concentration levels of nitrate in both anoxic and aerobic zones of a pre-denitrifying activated sludge plant, aiming to improve the nitrogen (N)removal from wastewater. The synthesis of the MPC controller is based on a l...

Offset-free multistep nonlinear model predictive control under plant–model mismatch

1College of Information and Control Engineering, China University of Petroleum (East China), Dongying, Shandong 257061, China 2Department of Automation, Tsinghua University, Beijing 10084, China 3Electronics and Computer Science, Faculty of Physical and Applied Sciences, University of Southampton, Southampton SO17 1BJ, UK 4Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi A...

Detection of Significant Model-Plant Mismatch from Routine Operation Data of Model Predictive Control System

The maintenance of model predictive control (MPC) systems is one of the major problems identified by industrial process control engineers. Since performance deterioration is usually caused by changes in process characteristics, effective re-modeling is the key to success. Obviously, not all sub-models have to be reconstructed; thus, it is crucial to identify sub-models that have significant mod...