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- G François, B Srinivasan, D Bonvin
- 2004

Process measurements can be used in an optimization framework to compensate the effects of run-time uncertainty. Among the various options for input adap-tion, a promising approach consists of directly enforcing the Necessary Conditions of Optimality (NCO) that include two parts: the active constraints and the sensitivities. In this paper, the variations of… (More)

- D Bonvin, B Srinivasan, D Ruppen
- 2002

Dynamic optimization of batch processes has attracted more attention in recent years since, in the face of growing competition , it is a natural choice for reducing production costs, improving product quality, and meeting safety requirements and environmental regulations. Since the models currently available in industry are poor and carry a large amount of… (More)

- G François, B Srinivasan, D Bonvin
- 2001

Run-to-run optimization exploits the repetitive nature of batch processes to adapt the optimal operating policy in the presence of uncertainty. For problems where terminal constraints play a dominant role in optimization, the system can be operated close to the optimum simply by satisfying terminal constraints. The optimal input is parameterized by using… (More)

In run-to-run control, measurements from previous runs are used to push the outputs of the current run towards desired set points. From a run-to-run perspective, the classical dynamics get integrated by each run, thereby leading to a static nonlinear input-output map. This paper shows that, when successive linearization of this nonlinear map is used to… (More)

- J-Y Favez, B Srinivasan, D Mullhaupt, Bonvin
- 2002

Bifurcation of the region of attraction for planar systems with one stable and one unstable pole under saturated linear state feedback is considered. The boundary of the region of attraction can either possess an unbounded hyperbolic shape or be a bounded limit cycle. The main contribution of this paper is to provide an analytical condition under which… (More)

- K Guemghar, B Srinivasan, D Bonvin
- 2003

The problem of controlling nonlinear nonminimum-phase systems is considered, where standard input-output feedback lin-earization leads to unstable internal dynamics. This problem is handled here by using the observability normal form in conjunction with input-output linearization. The system is feedback linearized upon neglecting a part of the system… (More)

- J-Y Favez, Ph Mullhaupt, B Srinivasan, J B Lister, D Bonvin
- 2003

— The control of the ITER tokamak unstable vertical position is considered in the presence of actuator saturation. Linearised models of the ITER system all share the feature of a single unstable pole (attributable to the vertical instability) and a large number of stable poles. The aim of this work is to improve the existing controller in the sense of… (More)

- L Bodizs, B Srinivasan, D Bonvin
- 2010

Integral observers are useful tools for estimating the plant states in the presence of non-vanishing disturbances resulting from plant-model mismatch and exogenous disturbances. It is well known that these observers can eliminate bias in all states, given that as many independent measurements are available as there are independent sources of disturbance. In… (More)

- L Bodizs, M Titica, N Faria, B Srinivasan, D Dochain, D Bonvin
- 2007

Industrial filamentous fungal fermentations are typically operated in fed-batch mode. Oxygen control represents an important operational challenge due to the varying biomass concentration. In this study, oxygen control is implemented by manipulating the substrate feed rate, i.e. the rate of oxygen consumption. It turns out that the setpoint for dissolved… (More)

- K Guemghar, B Srinivasan, D Bonvin
- 2005

In applying nonlinear model-predictive control to fast unstable systems, the main difficulty is that the optimization cannot be finished within one sampling interval. To solve this problem, a cascade-control scheme has been proposed, where input-output feedback linearization forms the inner loop and nonlinear predictive control the outer loop. Thus, the… (More)