Imperial College London
Alternate

ProfessorBenoitChachuat

Faculty of Engineering, Department of Chemical Engineering

Professor of Process Systems Engineering
 
 
 
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Contact

 

b.chachuat Website

 
 
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Location

 

609Roderic Hill BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
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203 results found

Deshpande S, Bonvin D, Chachuat B, 2010, Selective Input Adaptation in Parametric Optimal Control Problems involving Terminal Constraints, American Control Conference, Publisher: IEEE, Pages: 4782-4787, ISSN: 0743-1619

Conference paper

Chachuat B, Srinivasan B, Bonvin D, 2009, Adaptation strategies for real-time optimization, COMPUTERS & CHEMICAL ENGINEERING, Vol: 33, Pages: 1557-1567, ISSN: 0098-1354

Journal article

Mitsos A, Chachuat B, Barton PI, 2009, Towards global bilevel dynamic optimization, JOURNAL OF GLOBAL OPTIMIZATION, Vol: 45, Pages: 63-93, ISSN: 0925-5001

Journal article

Marchetti A, Chachuat B, Bonvin D, 2009, Modifier-Adaptation Methodology for Real-Time Optimization, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 48, Pages: 6022-6033, ISSN: 0888-5885

Journal article

Michalik C, Chachuat B, Marquardt W, 2009, Incremental Global Parameter Estimation in Dynamical Systems, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 48, Pages: 5489-5497, ISSN: 0888-5885

Journal article

Chachuat B, 2009, Optimal Design and Steady-State Operation, Pages: 199-222

Journal article

Marchetti A, Chachuat B, Bonvin D, 2009, Real-time optimization with estimation of experimental gradients, IFAC Proceedings Volumes (IFAC-PapersOnline), Vol: 7, Pages: 524-529, ISSN: 1474-6670

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 uses experimental gradient information and does not require the model parameters to be estimated on-line. 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 in simulation via the real-time optimization of a continuous reactor.

Journal article

Mitsos A, Chachuat B, Barton PI, 2009, McCormick-Based Relaxations of Algorithms, SIAM Journal on Optimization, Vol: 20, Pages: 573-601, ISSN: 1052-6234

Theory and implementation for the global optimization of a wide class of algorithms is presented via convex/affine relaxations. The basis for the proposed relaxations is the systematic construction of subgradients for the convex relaxations of factorable functions by McCormick [Math. Prog., 10 (1976), pp. 147-175]. Similar to the convex relaxation, the subgradient propagation relies on the recursive application of a few rules, namely, the calculation of subgradients for addition, multiplication, and composition operations. Subgradients at interior points can be calculated for any factorable function for which a McCormick relaxation exists, provided that subgradients are known for the relaxations of the univariate intrinsic functions. For boundary points, additional assumptions are necessary. An automated implementation based on operator overloading is presented, and the calculation of bounds based on a. ne relaxation is demonstrated for illustrative examples. Two numerical examples for the global optimization of algorithms are presented. In both examples a parameter estimation problem with embedded differential equations is considered. The solution of the differential equations is approximated by algorithms with a fixed number of iterations.

Journal article

Gros S, Srinivasan B, Chachuat B, Bonvin Det al., 2009, Neighbouring-extremal control for singular dynamic optimisation problems. Part I: single-input systems, INTERNATIONAL JOURNAL OF CONTROL, Vol: 82, Pages: 1099-1112, ISSN: 0020-7179

Journal article

Gros S, Chachuat B, Bonvin D, 2009, Neighbouring-extremal control for singular dynamic optimisation problems. Part II: multiple-input systems, INTERNATIONAL JOURNAL OF CONTROL, Vol: 82, Pages: 1193-1211, ISSN: 0020-7179

Journal article

Deshpande S, Chachuat B, Bonvin D, 2009, Parametric Sensitivity of Path-Constrained Optimal Control: Towards Selective Input Adaptation, American Control Conference 2009, Publisher: IEEE, Pages: 349-+, ISSN: 0743-1619

Conference paper

Radivojevic A, Chachuat B, Bonvin D, Hatzimanikatis Vet al., 2008, Study of tricyclic cascade networks using dynamic optimization

Conference paper

Mitsos A, Chachuat B, Barton PI, 2008, Global optimization of algorithms

Conference paper

Gros S, Chachuat B, Bonvin D, 2008, NCO tracking for singular control problems using neighboring extremals, IFAC Proceedings Volumes (IFAC-PapersOnline), Vol: 17, ISSN: 1474-6670

A powerful approach for dynamic optimization in the presence of uncertainty is to incorporate measurements into the optimization framework so as to track the necessary conditions of optimality (NCO), the so-called NCO-tracking approach. For nonsingular control problems, this can be done by tracking active constraints along boundary arcs, and using neighboring-extremal (NE) control along interior arcs to force the first-order variation of the NCO to zero. In this paper, an extension of NE control to singular control problems is proposed. The idea is to design NE controllers from successive time differentiations of the first-order variation of the NCO. Based on these results, a NCO-tracking controller that is easily tractable from a real-time optimization perspective is proposed, whose application guarantees that the first-order variation of the NCO converges to zero exponentially. The performance of this NCO-tracking controller is illustrated via the case study of a steered car, a 5th-order two-input dynamical system. Copyright © 2007 International Federation of Automatic Control All Rights Reserved.

Journal article

Marchetti A, Chachuat B, Bonvin D, 2008, Estimation of experimental gradients for real-time optimization

Conference paper

Mitsos A, Lemonidis P, Bollas GM, Chachuat B, Barton PIet al., 2008, A bilevel framework for process design & operation

Conference paper

Yunt M, Chachuat B, Mitsos A, Barton PIet al., 2008, Designing man-portable power generation systems for varying power demand, AICHE JOURNAL, Vol: 54, Pages: 1254-1269, ISSN: 0001-1541

Journal article

Chachuat B, Marchetti A, Bonvin D, 2008, Process optimization via constraints adaptation, JOURNAL OF PROCESS CONTROL, Vol: 18, Pages: 244-257, ISSN: 0959-1524

Journal article

Marchetti A, Chachuat B, Bonvin D, 2008, Real-Time Optimization via Adaptation and Control of the Constraints, 18th European Symposium on Computer Aided Process Engineering (ESCAPE-18), Publisher: ELSEVIER SCIENCE BV, Pages: 393-398, ISSN: 1570-7946

Conference paper

Chachuat B, Barton PI, 2008, Numerical simulation of a class of PDAEs with a separation of time scales, 14th European Conference for Mathematics in Industry, Publisher: SPRINGER-VERLAG BERLIN, Pages: 512-+, ISSN: 1612-3956

Conference paper

Chachuat B, Srinivasan B, Bonvin D, 2008, Model Parameterization Tailored to Real-time Optimization, 18th European Symposium on Computer Aided Process Engineering (ESCAPE-18), Publisher: ELSEVIER SCIENCE BV, Pages: 1-13, ISSN: 1570-7946

Conference paper

Mitsos A, Chachuat B, Barton PI, 2007, Methodology for the design of man-portable power generation devices, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 46, Pages: 7164-7176, ISSN: 0888-5885

Journal article

Mitsos A, Chachuat B, Barton PI, 2007, Microfabricated fuel cell systems: Beyond process synthesis, ABSTR PAP AM CHEM S, Vol: 234, ISSN: 0065-7727

Journal article

Marchetti AG, Chachuat, Bonvin D, 2007, Batch process optimization via run-to-run constraints adaptation, European Control Conference (ECC), Publisher: IEEE, Pages: 2791-2798

© 2007 EUCA. In the batch process industry, the available models carry a large amount of uncertainty and can seldom be used to directly optimize real processes. Several measurement-based optimization methods have been proposed to deal with model mismatch and process disturbances. Constraints often play a dominant role in the dynamic optimization of batch processes. In their presence, the optimal input profiles are characterized by a set of arcs, switching times and active path and terminal constraints. This paper presents a novel method tailored to those problems where the potential of optimization arises mainly from the correct set of path and terminal constraints being active. The input profiles are computed between successive runs by dynamic optimization of a fixed nominal model, and the constraints in the optimization problem are adapted using measured information from previous batches. Note that, unlike many existing optimization schemes, the measurements are not used to update the process model. Moreover, the proposed approach has the potential to uncover the optimal input structure. This is demonstrated on a simple semi-batch reactor example.

Conference paper

Mitsos A, Chachuat B, Barton PI, 2007, What is the design objective for portable power generation: Efficiency or energy density?, JOURNAL OF POWER SOURCES, Vol: 164, Pages: 678-687, ISSN: 0378-7753

Journal article

Bernard O, Chachuat B, Steyer JP, 2007, State Estimation for Wastewater Treatment Processes, Wastewater Quality Monitoring and Treatment, Pages: 247-263, ISBN: 9780471499299

Book chapter

Marchetti A, Chachuat B, Bonvin D, 2007, Real-time optimization of continuous processes via constraints adaptation, Pages: 45-50, ISSN: 1474-6670

In the framework of process optimization, measurements can be used to compensate for the effect of uncertainty. The method studied in this paper combines a process model and measurements to iteratively improve the operation of continuous processes. Unlike many existing real-time optimization schemes, the measurements are not used to update the process model, but to adapt the constraints in the optimization problem. Upon convergence, all the constraints are respected even in the presence of large model mismatch. Moreover, it is shown that constraints adaptation can handle changes in the set of active constraints. The approach is illustrated, via numerical simulation, for the optimization of a continuous stirred-tank reactor.

Conference paper

Chachuat B, Singer AB, Barton PI, 2006, Global methods for dynamic optimization and mixed-integer dynamic optimization, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 45, Pages: 8373-8392, ISSN: 0888-5885

Journal article

Chachuat B, Bernard O, 2006, Probabilistic observers for a class of uncertain biological processes, INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Vol: 16, Pages: 157-171, ISSN: 1049-8923

Journal article

Bernard O, Chachuat B, Hélias A, Rodriguez- Jet al., 2006, Can we assess the model complexity for a bioprocess:: theory and example of the anaerobic digestion process, WATER SCIENCE AND TECHNOLOGY, Vol: 53, Pages: 85-92, ISSN: 0273-1223

Journal article

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