A robust NMPC scheme for semi-batch polymerization reactors

Jang, Hong; Lee, Jay H.; Biegler, Lorenz T.

doi:10.1016/j.ifacol.2016.07.213

Cited by 30 publications

(18 citation statements)

References 15 publications

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“…One of the main goals is to reduce the variability among the produced batches despite the present uncertainties and disturbances. This problem struck the attention of many research groups (Nagy and Braatz, 2003;Srinivasan et al, 2003a;Adetola et al, 2009;François and Bonvin, 2013;Lucia et al, 2013;Martí et al, 2015;Jang et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Dynamic real-time optimization of batch processes using Pontryagin’s minimum principle and set-membership adaptation

Paulen

Fikar

2019

Computers & Chemical Engineering

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This paper studies a dynamic real-time optimization in the context of modelbased time-optimal operation of batch processes under parametric model mismatch. In order to tackle the model-mismatch issue, a receding-horizon policy is usually followed with frequent re-optimization. The main problem addressed in this study is the high computational burden that is usually required by such schemes. We propose an approach that uses parameterized conditions of optimality in the adaptive predictive-control fashion. The uncertainty in the model predictions is treated explicitly using reachable sets that are projected into the optimality conditions. Adaptation of model parameters is performed online using set-membership estimation. A class of batch membrane separation processes is in the scope of the presented applications, where the benefits of the presented approach are outlined.

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Section: Introductionmentioning

confidence: 99%

Dynamic real-time optimization of batch processes using Pontryagin’s minimum principle and set-membership adaptation

Paulen

Fikar

2019

Computers & Chemical Engineering

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“…(Lucia et al, 2013) suggested a multi-stage NMPC scheme to deal with uncertainties, and a scenario-tree approach was used to optimize a semi-batch polymerization reactor. Recently, (Jang et al, 2016) proposed a multi-stage NMPC scheme for semi-batch reactors using backoffs on path constraints. (Binette and Srinivasan, 2016) compared the performance of different tracking objectives for the NMPC of batch processes without parameters adaptation.…”

Section: Introductionmentioning

confidence: 99%

“…Since the states are approximated instead of integrated, these approaches are called 'infeasible-path' methods. Direct simultaneous methods were reported to be effective for large-scale optimization and continuous NMPC problems in the literature Biegler et al, 2002;Wächter and Biegler, 2006;Kameswaran and Biegler, 2006;Biegler, 2007;Huang et al, 2009;Jang et al, 2016). (Zavala and Biegler, 2009) introduced an 'advanced-step' DSM to deal with the feedback delay associated with the time required to compute the solution.…”

Section: Introductionmentioning

confidence: 99%

NMPC using Pontryagin’s Minimum Principle-Application to a two-phase semi-batch hydroformylation reactor under uncertainty

Aydın

Bonvin

Sundmacher

2018

Computers & Chemical Engineering

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Nonlinear model predictive control (NMPC) is an important tool to perform real-time optimization for batch and semi-batch processes. Direct methods are often the methods of choice to solve the corresponding optimal control problems, in particular for large-scale problems. However, the matrix factorizations associated with large prediction horizons can be computationally demanding. In contrast, indirect methods can be competitive for smallerscale problems. Furthermore, the interplay between states and co-states in the context of Pontryagin's Minimum Principle might turn out to be computationally quite efficient. This work proposes to use an indirect solution technique within shrinking-horizon in the context of NMPC. In particular, the technique deals with path constraints via indirect adjoining, which allows meeting active path constraints explicitly at each iteration. Uncertainties are handled by the introduction of time-varying backoff terms for the path 2 constraints. The resulting NMPC algorithm is applied to a two-phase semi-batch reactor for the hydroformylation of 1-dodecene in the presence of uncertainty, and its performance is compared to that of NMPC that uses a direct simultaneous optimization method. The results show that the proposed algorithm (i) can enforce feasible operation for different uncertainty realizations both within batch or from batch to batch, and (ii) it is significantly faster than direct simultaneous NMPC, especially at the beginning of the batch. In addition, a modification of the PMP-based NMPC scheme is proposed that enforces active constraints via tracking.

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“…Unlike continuous operation around a steady state, the large variation in operating conditions encountered during a batch results in the modeling, control, and optimization of batch operations having to grapple more with challenges such as nonlinear process dynamics and constraints. Among existing batch control formulations, some assume knowledge of a first principles model, while the primary contribution in others is the identification and utilization of data‐driven models for batch process control.…”

Section: Introductionmentioning

confidence: 99%

Handling sensor faults in economic model predictive control of batch processes

et al. 2018

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The problem of sensor fault detection and isolation (FDI) and fault‐tolerant economic model predictive control (FT‐EMPC) for batch processes is addressed. To this end, we first model batch processes using subspace‐based system identification techniques. The analytical redundancy within the identified model is subsequently exploited to detect, isolate, and handle the faulty measurements. The reconciled fault‐free measurements are then incorporated in an economic model predictive controller formulation. Simulation case studies involving the application of the proposed data‐driven FDI and FT‐EMPC algorithms to the energy intensive electric arc furnace process illustrate the improvement in economic performance under various fault scenarios. © 2018 American Institute of Chemical Engineers AIChE J, 65: 617–628, 2019

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A robust NMPC scheme for semi-batch polymerization reactors

Cited by 30 publications

References 15 publications

Dynamic real-time optimization of batch processes using Pontryagin’s minimum principle and set-membership adaptation

Dynamic real-time optimization of batch processes using Pontryagin’s minimum principle and set-membership adaptation

NMPC using Pontryagin’s Minimum Principle-Application to a two-phase semi-batch hydroformylation reactor under uncertainty

Handling sensor faults in economic model predictive control of batch processes

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