Stochastic model predictive control with active uncertainty learning: A survey on dual control
A Mesbah - Annual Reviews in Control, 2018 - Elsevier
This paper provides a review of model predictive control (MPC) methods with active
uncertainty learning. System uncertainty poses a key theoretical and practical challenge in …
uncertainty learning. System uncertainty poses a key theoretical and practical challenge in …
An overview of control performance assessment technology and industrial applications
M Jelali - Control engineering practice, 2006 - Elsevier
A review of the current status in control performance assessment (CPA) technology and
industrial applications is presented. Merits and drawbacks of each CPA method are …
industrial applications is presented. Merits and drawbacks of each CPA method are …
[LIVRE][B] Practical PID control
A Visioli - 2006 - books.google.com
Proportional–integral–derivative (PID) controllers are the most adopted controllers in
industrial settings because of the advantageous cost/benefit ratio they are able to provide …
industrial settings because of the advantageous cost/benefit ratio they are able to provide …
[LIVRE][B] Dynamic modeling, predictive control and performance monitoring: a data-driven subspace approach
B Huang, R Kadali - 2008 - books.google.com
A typical design procedure for model predictive control or control performance monitoring
consists of: identification of a parametric or nonparametric model; derivation of the output …
consists of: identification of a parametric or nonparametric model; derivation of the output …
Control performance management in industrial automation: assessment, diagnosis and improvement of control loop performance
M Jelali - 2012 - books.google.com
Control Performance Management in Industrial Automation provides a coherent and self-
contained treatment of a group of methods and applications of burgeoning importance to the …
contained treatment of a group of methods and applications of burgeoning importance to the …
Detection of model-plant mismatch in MPC applications
In model predictive control of processes, the process model plays an important role. The
performance of the controller depends on the quality of the model and hence on the model …
performance of the controller depends on the quality of the model and hence on the model …
Multivariable MPC system performance assessment, monitoring, and diagnosis
J Schäfer, A Cinar - Journal of process control, 2004 - Elsevier
This study focuses on performance assessment and monitoring of model predictive control
systems. A methodology is proposed to determine a benchmark and monitor model …
systems. A methodology is proposed to determine a benchmark and monitor model …
Recent developments in multivariable controller performance monitoring
In this paper, we give a critical overview of recent development in MIMO control performance
monitoring. We discuss a number of MIMO control benchmarks including minimum variance …
monitoring. We discuss a number of MIMO control benchmarks including minimum variance …
Performance monitoring of model-predictive controllers via model residual assessment
Model quality is a main factor that affects the control performance of model-based
controllers. In this paper, a new closed-loop model assessment approach is proposed to …
controllers. In this paper, a new closed-loop model assessment approach is proposed to …
Quantifying the impact of model-plant mismatch on controller performance
In model predictive control (MPC) of processes, the model fidelity plays an important role.
The performance of MPC depends on the quality of the model and hence on the model-plant …
The performance of MPC depends on the quality of the model and hence on the model-plant …