Model adequacy requirements for optimizing plant operations

Forbes, J. Fraser; Marlin, Thomas E.; MacGregor, John F.

doi:10.1016/0098-1354(93)e0005-t

Cited by 113 publications

(104 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This reactor example has also been used to illustrate model adequacy and RTO performance [15,16]. It consists of an ideal CSTR in which the following reactions occur:…”

Section: Reactor and Modelmentioning

confidence: 99%

See 1 more Smart Citation

A dual modifier-adaptation approach for real-time optimization

Marchetti

Chachuat

Bonvin

2010

Journal of Process Control

122

142

View full text Add to dashboard Cite

For good performance in practice, real-time optimization schemes need to be able to deal with the inevitable plant-model mismatch problem. Unlike the two-step schemes combining parameter estimation and optimization, the modifier-adaptation approach does not require the model parameters to be estimated on-line. Instead, it uses information regarding the constraints and selected gradients to improve the plant operation. The dual modifier-adaptation approach presented in this paper drives the process towards optimality, while paying attention to the accuracy of the estimated gradients. The gradients are estimated from successive operating points generated by the optimization algorithm. The novelty lies in the development of an upper bound on the norm of the gradient errors, which is used as a constraint when determining the next operating point. The proposed approach is demonstrated via numerical simulation for both an unconstrained and a constrained problem. A Dual Modifier-Adaptation Approach forReal-Time Optimization AbstractFor good performance in practice, real-time optimization schemes need to be able to deal with the inevitable plant-model mismatch problem. Unlike the two-step schemes combining parameter estimation and optimization, the modifier-adaptation approach does not require the model parameters to be estimated on-line. Instead, it uses information regarding the constraints and selected gradients to improve the plant operation. The dual modifier-adaptation approach presented in this paper drives the process towards optimality, while paying attention to the accuracy of the estimated gradients. The gradients are estimated from successive operating points generated by the optimization algorithm. The novelty lies in the development of an upper bound on the norm of the gradient errors, which is used as a constraint when determining the next operating point. The proposed approach is demonstrated via numerical simulation for both an unconstrained and a constrained problem.

show abstract

“…This reactor example has also been used to illustrate model adequacy and RTO performance [15,16]. It consists of an ideal CSTR in which the following reactions occur:…”

Section: Reactor and Modelmentioning

confidence: 99%

“…However, since it is assumed that the reaction system is not well understood, the following two reactions are used in the model of the reactor [15]:…”

Section: Reactor and Modelmentioning

confidence: 99%

A dual modifier-adaptation approach for real-time optimization

Marchetti

Chachuat

Bonvin

2010

Journal of Process Control

122

142

View full text Add to dashboard Cite

show abstract

“…The first widely available RTO approach was the twostep approach that adapts the model parameters on the basis of differences between predicted and measured outputs and uses the updated process model to re-compute the optimal inputs 66,67 . However, in the presence of structural plant-model mismatch, this method is very unlikely to drive the plant to optimality 68,69 . Hence, alternatives to the two-step approach have recently been developed.…”

Section: Eq (29)mentioning

confidence: 99%

Control and Optimization of Batch Chemical Processes

Bonvin

François

2017

Coulson and Richardson's Chemical Engineering

View full text Add to dashboard Cite

A batch process is characterized by the repetition of time-varying operations of finite duration. Due to the repetition, there are two independent "time" variables, namely, the run time during a batch and the batch index. Accordingly, the control and optimization objectives can be defined for a given batch or over several batches. This chapter describes the various control and optimization strategies available for the operation of batch processes. These include online and run-to-run control on the one hand, and repeated numerical optimization and optimizing control on the other. Several case studies are presented to illustrate the various approaches Keywords Batch control, predictive control, iterative learning control, run-to-run control, batch process optimization, dynamic optimization, optimizing control, run-to-run optimization.

show abstract

“…The key feature of MA is to modify the necessary conditions of optimality (NCO) predicted by the model via input-affine corrections to the cost and constraint functions. As a result, the adequacy conditions [14] are much easier to meet than the corresponding conditions for the two-step approach [15], especially in the case of structural plant-model mismatch. This is a very valuable property since structural mismatch is almost invariably present in complex plants (i.e., there are always simplifying assumptions made during the modeling stage).…”

Section: Introductionmentioning

confidence: 99%

Extension of modifier adaptation for controlled plants using static open-loop models

François

Costello

Marchetti

et al. 2016

Computers & Chemical Engineering

View full text Add to dashboard Cite

Model-based optimization methods suffer from the limited accuracy of the available process models. Because of plant-model mismatch, model-based optimal inputs may be suboptimal or, worse, unfeasible for the plant. Modifier adaptation (MA) overcomes this obstacle by incorporating measurements in the optimization framework. However, the standard MA formulation requires that (1) the model satisfies adequacy conditions and (2) the model and the plant share the same degrees of freedom. In this article, three extensions of MA to problems where (2) does not hold are proposed. In particular, we consider the case of controlled plants for which the only a model of the open-loop plant is available. These extensions are shown to preserve the ability of MA to converge to the plant optimum despite disturbances and plant-model mismatch. The proposed methods are illustrated in simulation for the optimization of a CSTR.

show abstract

Model adequacy requirements for optimizing plant operations

Cited by 113 publications

References 6 publications

A dual modifier-adaptation approach for real-time optimization

A dual modifier-adaptation approach for real-time optimization

Control and Optimization of Batch Chemical Processes

Extension of modifier adaptation for controlled plants using static open-loop models

Contact Info

Product

Resources

About