S. Azevedo

发表

Databank transfer-of-information, shortcut and exact estimators used in the wastewater biological treatment process identification

Sebastião Feyo de Azevedo, Romualdo Salcedo, Cristina Maria, 2000 .

LINEAR MODEL PREDICTIVE CONTROL STRATEGIES APPLIED TO A BATCH SUGAR CRYSTALLIZER

S. Azevedo, P. Georgieva, L. S. Dediós, 2006 .

Model Predictive Control Strategies for Batch Sugar Crystallization Process

S. Azevedo, P. Georgieva, L. A. P. Suárez, 2011 .

Nonlinear model predictive control strategies applied to a fed-bath sugar crystallizer

S. Azevedo, P. Georgieva, L. S. Dediós, 2007 .

Stability, dynamics of convergence and tuning of observer-based kinetics estimators

Eugénio C. Ferreira, S. Feyo de Azevedo, S. Azevedo, 2002 .

Monitoring crystallization. I: On-line monitoring of white sugar crystallization through software sensors

S. Feyo de Azevedo, S. Azevedo, M. J. Gonçalves, 1993 .

Dynamical model of brushite precipitation

Cristina C. Oliveira, S. Azevedo, A. Ferreira, 2007 .

PROCESS CONTROL

S. Azevedo, Rui Oliveira, P. Fox, 2004 .

A new hybrid modeling methodology based on delayed differential equations : Application to antibody expression by Pichia pastoris

S. Azevedo, M. Stosch, J. Peres, 2008 .

DESIGN ASPECTS OF CATALYTIC REACTORS AND ADSORBERS

S. Azevedo, C. Costa, A. Rodrigues, 1984 .

Computer-Based Studies on Bioprocess Engineering

S. Feyo de Azevedo, Eugénio C. Ferreira, Pedro Pimenta, 1996 .

Computer-based studies on bioprocess engineering : II - Tools for process operation

Eugénio C. Ferreira, Filomena Soares, S. Feyo de Azevedo, 1996 .

Optimal selection of orthogonal polynomials applied to the integration of chemical reactor equations by collocation methods

Denis Dochain, Laurent Lefèvre, S. Feyo de Azevedo, 2000 .

Error Tolerant Predictive Control Based on Recurrent Neural Models

Petia Georgieva, Sebastião Feyo de Azevedo, S. Azevedo, 2014, Innovations in Intelligent Machines.

Neural networks for model predictive control

Petia Georgieva, Sebastião Feyo de Azevedo, S. Azevedo, 2011, The 2011 International Joint Conference on Neural Networks.

NEURAL NETWORK MODEL PREDICTIVE CONTROL APPLIED TO A FED-BATCH SUGAR CRYSTALLIZATION

S. Azevedo, P. Georgieva, L. A. P. Suárez, 2009 .

SISO versus MIMO model based predictive control structures: a fed-batch crystallizer case study

Petia Georgieva, Sebastião Feyo de Azevedo, Luis Sanchez Dedios, 2008 .

Bioprocess hybrid parametric/nonparametric modelling based on the concept of mixture of experts

S. Feyo de Azevedo, Rui Oliveira, J. Peres, 2008 .

Hybrid Modelling of Fermentation Processes: A Study on the Use of Modular Neural Networks for Modelling Cells Reaction Kinetics

S. Feyo de Azevedo, Rui Oliveira, J. Peres, 2004 .

A novel identification method for hybrid (N)PLS dynamical systems with application to bioprocesses

Sebastião Feyo de Azevedo, Moritz von Stosch, Rui Oliveira, 2011, Expert Syst. Appl..

Sensitivity analysis concerning the design and operation of a tubular fixed-bed catalytic reactor

S. Feyo de Azevedo, A. P. Wardle, S. Azevedo, 1989 .

Nonlinear MPC for fed-batch multiple stages sugar crystallization

Petia Georgieva, Sebastião Feyo de Azevedo, Luis Alberto Paz Suarez, 2011 .

Generalized Predictive Control of a Batch Evaporative Crystallizer

S. Feyo de Azevedo, Kaddour Najim, V. Ruiz, 1989 .

A general hybrid semi-parametric process control framework

Sebastião Feyo de Azevedo, Moritz von Stosch, Rui Oliveira, 2012 .

Hybrid semi-parametric modeling in process systems engineering: Past, present and future

Sebastião Feyo de Azevedo, Moritz von Stosch, Rui Oliveira, 2014, Comput. Chem. Eng..

Dynamic Optimisation of Industrial Sugar Crystallization Process based on a Hybrid (mechanistic+ANN) Model

Petia Georgieva, Sebastião Feyo de Azevedo, Vytautas Galvanauskas, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Modelling biochemical networks with intrinsic time delays: a hybrid semi-parametric approach

Sebastião Feyo de Azevedo, Moritz von Stosch, Rui Oliveira, 2010, BMC Systems Biology.

Quantification of the morphology of sucrose crystals by image analysis

S. Azevedo, M. Pons, H. Vivier, 2003 .

On-line tuning of a neural PID controller based on plant hybrid modeling

Sebastião Feyo de Azevedo, Alojz Mészáros, A. Andrásik, 2004, Comput. Chem. Eng..

MODELLING OF TUBULAR FIXED-BED CATALYTIC REACTORS : A BRIEF REVIEW

S. Feyo de Azevedo, M. A. Romero-Ogawa, A. P. Wardle, 1990 .

On-line monitoring of a sugar crystallization process

Julian Morris, A. Simoglou, Petia Georgieva, 2005, Comput. Chem. Eng..

Which Education of Chemical Engineers in 2020? 1

Roberto Frias, Sebastião Feyo de Azevedo, Roberto Frias, 2001 .

Hybrid modelling of a PHA production process using modular neural networks

Rui Oliveira, S. Feyo de Azevedo, Luísa S. Serafim, 2004 .

Preliminary Results From SILVVER '03 - Seismic Investigations of the Las Vegas Valley: Evaluating Risk

John P. Lewis, S. Azevedo, A. Rodgers, 2003 .

Intelligent Predictive Control - Application to Scheduled Crystallization Processes

Petia Georgieva, Sebastião Feyo de Azevedo, Luis Alberto Paz Suarez, 2009, 2009 International Conference on Adaptive and Intelligent Systems.

Error tolerant MPC versus PI control - a crystallization case study

Petia Georgieva, Sebastião Feyo de Azevedo, Luis Alberto Paz Suárez, 2009, 2009 European Control Conference (ECC).

Computationally efficient process control with neural networkbased predictive models

Petia Georgieva, Sebastião Feyo de Azevedo, Luis A. Paz Suarez, 2009, 2009 International Joint Conference on Neural Networks.

Knowledge-based hybrid modelling of a batch crystallisation when accounting for nucleation, growth and agglomeration phenomena

Petia Georgieva, S. Feyo de Azevedo, M. J. Meireles, 2003 .

USING IMAGE ANALYSIS TO LOOK INTO THE EFFECT OF IMPURITY CONCENTRATION IN NACL CRYSTALLIZATION

S. Azevedo, A. Lopes, F. Rocha, 2005 .

HYBNET, An Advanced Tool for Process Optimization and Control

Rimvydas Simutis, S. Feyo de Azevedo, Andreas Lübbert, 1998 .

Modelling agglomeration degree in sucrose crystallisation

Marie-Noëlle Pons, S. Feyo de Azevedo, Fernando Rocha, 2008 .

Tuning of observer-based estimators: theory and application to the on-line estimation of kinetic parameters

Denis Dochain, Michel Perrier, Eugénio C. Ferreira, 2000 .

Neural Network-Based Control Strategies Applied to a Fed-Batch Crystallization Process

Petia Georgieva, S. Feyo de Azevedo, S. Azevedo, 2007 .

Robust control design of an activated sludge process

Petia Georgieva, S. Feyo de Azevedo, S. Azevedo, 1999 .

Hydrodynamic and Kinetic Modelling of a Flocculating Bioreactor with Cell Recycle

S. Azevedo, J. Teixeira, M. Mota, 1989 .

Neural Network-Based Control Strategies Applied to a Fed-Batch Crystallization Process

S. Azevedo, P. Georgieva, 2007 .

Optimal monitoring and risk limits for a wastewater biological treatment serial plant

G. Maria, C. Maria, R. Salcedo, 2001, 2001 European Control Conference (ECC).