Nuno M.C. Oliveira

An extension of Newton-type algorithms for nonlinear process control

This study extends the multistep, Newton-type formulation [Li and Biegler (1989) Chem. Eng. Res, Des., 67, 562–577]for nonlinear constrained process control. The computation of the control law is based on an augmented performance index, which improves the performance of the method over the original formulation. A number of modifications are also introduced in the computational algorithm to extend the range of problems, eliminate steady-state offsets, and extend the output predictive horizon to infinity. We show that the global stability properties of the original Newton controller are preserved by the present modifications. Moreover in the absence of active constraints, the method behaves as an extension of the linear quadratic regulator for, exhibiting therefore excellent stability properties for a large range of tuning parameters. The capabilities of the method are illustrated by application to various process examples.

Separation of ethanol–water mixtures by liquid–liquid extraction using phosphonium-based ionic liquids

Bio-alcohols are produced from biomass by fermentation, and distillation is commonly used to separate the alcohol from the aqueous phase. This is, however, a high energy consumption process, and alternative approaches to this separation are being pursued. In this work, the use of phosphonium-based ionic liquids (ILs) for the extraction of ethanol from fermentation broths is investigated. Ternary phase diagrams, necessary for the design and to implement an alternative liquid–liquid extraction process for the alcohol recovery, were determined for seven ionic liquids. The modelling of the equilibrium data was performed using the COSMO-RS and NRTL models; the first aiming at screening other ionic liquids not experimentally studied, and the latter aiming at designing a separation process. The gathered data indicate that phosphonium-based ionic liquids are the best yet reported to perform water–ethanol separations. Based on the most promising phase diagrams, an analysis of the alcohol and ionic liquid recovery steps was carried out and a liquid–liquid extraction stage coupled to an extractive fermentation, where the ionic liquid is continuously recycled to the fermentator and the ethanol concentration is carried out by pervaporation, is here proposed as an alternative to distillation.

Predictive methods for the estimation of thermophysical properties of ionic liquids

While the design of products and processes involving ionic liquids (ILs) requires knowledge of the thermophysical properties for these compounds, the massive number of possible distinct ILs precludes their detailed experimental characterization. To overcome this limitation, chemists and engineers must rely on predictive models that are able to generate reliable values for these properties, from the knowledge of the structure of the IL. A large body of literature was developed in the last decade for this purpose, aiming at developing predictive models for thermophysical and transport properties of ILs. A critical review of those models is reported here. The modelling approaches are discussed and suggestions relative to the current best methodologies for the prediction of each property are presented. Since most of the these works date from the last 5 years, this field can still be considered to be in its infancy. Consequently, this work also aims at highlighting major gaps in both existing data and modelling approaches, identifying unbeaten tracks and promising paths for further development in this area.

Reliable and Efficient Optimization Strategies for Nonlinear Model Predictive Control

Abstract Previous experience with predictive control algorithms has shown that the way the optimization problems are formulated and solved has a big impact in the success of the control strategy. Here a multiple shooting formulation is proposed, where a process model is integrated separately inside each sampling interval, and the corresponding equality constraints are added directly to the optimization problem. It is shown that the resulting formulation provides a more reliable framework for the solution of predictive control problems, both in the linear and nonlinear cases. This strategy is compared with the original nonlinear Newton-type (state space) algorithm, on a number of process models with challenging features, including the reactor model from the Tennessee Eastman problem.

Kinetic Models for the Homogeneous Alkaline and Acid Catalysis in Biodiesel Production

Abstract In this work, kinetic models were obtained from experimental data in the open literature, for both the alkaline (NaOH) and acid (H2SO4) homogeneous catalysis of the transesterification reaction, used to produce biodiesel from vegetable oils. Two approaches, designated as statistical and empirical, were adopted to obtain these models. For both catalysis types, the kinetic models obtained show average absolute errors of approximately 4%, using both empirical and statistical approaches, well within the precision of the experimental procedures. In the alkaline catalysis, kinetic models fitted better a pseudo 2nd-order reaction, while for the acid catalysis pseudo 1st-order reaction provided a best fit.

Model predictive control of a pilot plant reactor with a simulated exothermic reaction

Abstract The main goal of this work is to investigate the performance of a Receding Horizon Model Predictive Control scheme applied to a real plant. Nonlinear Model Predictive Control (MPC) algorithms have been described in the literature with great success when applied in simulation studies. However, simulation results do not always reflect the process realities, and they are often inadequate to guarantee that such sophisticated control algorithms can be applied in real plants. In this work, a linearized MPC control design has been experimentally used for temperature and level control in a CSTR. The process is unstable in open-loop, the variables are not all measured, while the process parameters are not very well known and can change with time. The experimental control tests were carried out in an industrial scale pilot plant where a pseudo zero order exothermic chemical reaction is partially simulated. The rate of heat generated by reaction is calculated and converted into an equivalent steam flowrate, which is injected in the mixture. A significant improvement in the controller performance is obtained with the MPC strategy, when compared with the previously existing PI based controller structure. The possibility of implementing the MPC in the corresponding industrial environment is outlined.

Optimization and nonlinear Model Predictive Control of batch polymerization systems

Abstract This paper addresses the optimization of batch polymerization systems, using a feasible path approach, with roots on Model Predictive Control (MPC) theory. The approach allows the reuse of many concepts previously developed for nonlinear MPC of continuous plants. It also provides an efficient and well-integrated methodology for the optimal supervision of discontinuous chemical processes. The application of this technique to the optimization of the batch suspension polymerization of vinyl chloride and the solution polymerization of methyl methacrylate is considered. Significant advantages associated to the use of this methodology are demonstrated with both examples, in terms of productivity gains and the capability of manufacturing products with pre-specified properties.

Closed-loop dynamic behavior of an industrial high-efficiency FCC unit

Although the control of an FCC plant includes all the hardware components of the process, it is at the FCC reactor-regenerator system that the control is the most critical. This is mainly due to the strong interaction between the reactor and regenerator units. As a result, the reactor-regenerator system presents a highly nonlinear behavior and is therefore a challenge for control tasks. This paper presents a brief introduction to the control of a high-efficiency FCC unit and the implementation of the main regulatory control loops in the reactor-regenerator system of a real Portuguese industrial high- efficiency FCC unit. Moreover, closed-loop dynamic simulations performed with a model previously developed by the same authors, are compared to industrial dynamic data from step tests done in GalpEnergia FCC unit showing that this FCC simulator can realistically represent the closed-loop dynamic behavior of a real industrial operating unit. Therefore, this dynamic model has a great potential to be used as a reference model for advanced model-based control and real-time optimization purposes.

Mechanistic Dynamic Modelling of an Industrial FCC Unit

Abstract The aim of this study is to obtain a model that can simulate the performance of an industrial Fluidised Catalytic Cracking (FCC) unit in steady and dynamic state and which will subsequently be used in studies of control and real time optimisation. In this paper, a dynamic model for a R2R type FCC unit is presented. The model includes the riser, the stripper/disengager, the regeneration system and the catalyst transport lines. Mass, energy and pressure balances are performed for each of these sections. Simulation results for steady and dynamic states are presented and compared qualitatively with those from previous FCC models.

Constrained Smoothing of Experimental Data in the Identification of Kinetic Models

Abstract In the context of the application of systematic methodologies for the incremental development of mechanistic kinetic models, various regularization techniques have been explored to allow the estimation of rate phenomena as the derivatives of sparse data sets. Through a combination of a numerical approach with aspects of qualitative analysis, this work proposes a novel method to obtain smoothed concentration profiles that allow their reliable differentiation. Two different case studies are considered to illustrate the performance of the method.