Adaptation strategies for real-time optimization

Chachuat, Benoît; Srinivasan, Balasubramaniam; Bonvin, Dominique

doi:10.1016/j.compchemeng.2009.04.014

Cited by 222 publications

(161 citation statements)

References 31 publications

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“…Hence, reaching optimal performance in the presence of plant-model mismatch is a difficult task, which necessitates adaptation based on measured information. A three-way classification of RTO schemes has recently been proposed in [2]. One class includes the socalled modifier-adaptation approach [3], whereby appropriate terms are added to the optimization problem and updated so that the KKT conditions of the model match those of the plant.…”

Section: Introductionmentioning

confidence: 99%

A dual modifier-adaptation approach for real-time optimization

Marchetti

Chachuat

Bonvin

2010

Journal of Process Control

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142

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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.

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Section: Introductionmentioning

confidence: 99%

A dual modifier-adaptation approach for real-time optimization

Marchetti

Chachuat

Bonvin

2010

Journal of Process Control

Self Cite

121

142

View full text Add to dashboard Cite

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“…Static optimization problems, 2. Steady-state optimization problems, for which the cost and constraints functions are defined at the steady state of some dynamical process, 3. Dynamic optimization problems that are reformulated as general NLPs, e.g.…”

Section: Formulation Of the Optimization Problemmentioning

confidence: 99%

Use of Convex Model Approximations for Real-Time Optimization via Modifier Adaptation

François

Bonvin

2013

Ind. Eng. Chem. Res.

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Real-Time Optimization (RTO) via modifier adaptation is a class of methods for which measurements are used to iteratively adapt the model via input-affine additive terms. The modifier terms correspond to the deviations between the measured and predicted constraints on the one hand, and the measured and predicted cost and constraint gradients on the other. If the iterative scheme converges, these modifier terms guarantee that the converged point satisfies the KKT conditions for the plant. Furthermore, if upon convergence the plant model predicts the correct curvature of the cost function, convergence to a (local) plant optimum is guaranteed.The main advantage of modifier adaptation lies in the fact that these properties do not rely on specific assumptions regarding the nature of the uncertainty. In other words, in addition to rejecting the effect of parametric uncertainty like most RTO methods, modifier adaptation can also handle process disturbances and structural plant-model mismatch. This paper shows that the use of a convex model approximation in the modifier-adaptation framework implicitly enforces model adequacy. The approach is illustrated through both a simple numerical example and a simulated continuous stirred-tank reactor.

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“…Na prática, raramente o modelo do processo pode ser ajustado com precisão elevada (CHACHUAT et al,2009), resultam incertezas ao tentar descrever um processo complexo através de um modelo de complexidade limitada. Jiang et al (2003) analisaram as tendências dos processos a partir dos dados medidos nas variáveis de operação, usando a análise de wavelets multiescala (wavelet multi-scale) para a detecção de estado estacionário em processos contínuos (JIANG et al, 2003).…”

Section: Otimização Em Tempo Real-rtounclassified

“…Muitos dos problemas na aplicação da otimização de processo em tempo real surgem da inabilidade para construir e adaptar modelos físico-químicos adequados para sistemas complexos de processamentos (CHACHUAT et al, 2009 Estes estimadores são bons candidatos para fazer a reconciliação e a estimação de parâmetros em uma etapa conjunta, pois eles suavizam o efeito da presença de erros grosseiros. Portanto, são os mais atrativos na aplicação da RTO para cumprir com as três etapas simultaneamente, requerendo somente duas otimizações definidas como se mostra na Figura 6.…”

Section: Estimação De Parâmetrosunclassified

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Metodologias de análise de dados para um sistema de otimização em tempo real.

García¹,

Marcela²

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Adaptation strategies for real-time optimization

Cited by 222 publications

References 31 publications

A dual modifier-adaptation approach for real-time optimization

A dual modifier-adaptation approach for real-time optimization

Use of Convex Model Approximations for Real-Time Optimization via Modifier Adaptation

Metodologias de análise de dados para um sistema de otimização em tempo real.

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