Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control

Part I - BASIC DETAILS AND STATE ESTIMATION ALGORITHMS 1.?Optimal state estimation and its importance in process systems engineering 2.?Stochastic process and filtering theory 3.?Linear filtering and observation techniques with examples 4.?Mechanistic model-based nonlinear filtering and observation techniques for state estimation 5.?Data-driven modelling techniques for state estimation 6.?Optimal sensor configuration methods for state estimation

Part II - APPLICATION OF MECHANISTIC MODEL-BASED NONLINEAR FILTERING AND OBSERVATION TECHNIQUES FOR STATE ESTIMATION IN CHEMICAL PROCESSES 7.?Optimal state estimation in multicomponent batch distillation 8.?Optimal state estimation in multicomponent reactive batch distillation with optimal sensor configuration 9.?Optimal state estimation in complex nonlinear dynamical systems 10.?Optimal state estimation of a kraft pulping digester? 11.?Optimal State Estimation of a High Dimensional Fluid Catalytic Cracking Unit 12.?Optimal state estimation of continuous distillation column with optimal sensor configuration 13.?Optimal state and parameter estimation in nonlinear CSTR

Part III - APPLICATION OF QUANTITATIVE MODEL-BASED NONLINEAR FILTERING AND OBSERVATION TECHNIQUES FOR STATE ESTIMATION IN BIOCHEMICAL PROCESSES 14.?Optimal state and parameter estimation in the nonlinear batch beer fermentation process 15.?Optimal state and parameter estimation for online optimization of an uncertain biochemical reactor

Part IV - APPLICATION OF DATA-DRIVEN MODEL-BASED TECHNIQUES FOR STATE ESTIMATION IN CHEMICAL PROCESSES 16.?Data-driven methods for state estimation in multi-component batch distillation 17.?Hybrid schemes for state estimation 18.?Future development, prospective and challenges in the application of soft sensors in industrial applications

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?Adaptive soft sensor; Artificial neural networks; Artificial neural networks (ANN); Automation; Batch distillation; Bayes filtering; Bifurcation; Bioprocess monitoring; Catalytic cracking unit; Catalytic tubular reactor; Chaos; Chaotic chemical reactor; Chemical reactor; Composition control; Composition estimation; Composition estimator; Continuous reactive distillation; Continuous system; Controllability; Covariance matrix; Data-driven modeling; Degree of observability; Delignification; Discrete Kalman filter; Discrete dynamic model; Discrete system; Distributed dynamic system; Distribution function; Dynamic mathematical model; Dynamic model; Dynamic process model; Dynamical systems; Empirical observability Grammian; Empirical observability gramian; Empirical observability grammian; Estimation; Estimator; Extended Kalman filter; Fault detection; Fault diagnosis; Genetic algorithm; High dimensional system; High-dimensional system; Homopolymerization reactor; Inferential measurements; Kalman filter; Kraft pulping process; Least squares; Linear systems; Luenberger observer; Mathematical model; Method of lines; Model identification; Model-based state estimation; Multiplicity; Nonlinear control; Nonlinear dynamics; Nonlinear iterative partial least squares; Nonlinear iterative partial least squares (NIPALS); Nonlinear observer; Nonlinear system; Observability; Observability of nonlinear system; Observer; Online optimization; Optimal composition estimation; Optimal operation; Optimal state estimation; Oscillations; PI controller; Parameter identification; Parametric sensitivity; Polymerization reactor; Prediction; Principal component analysis; Principal component analysis (PCA); Probability; Process control; Process industry; Process knowledge; Process monitoring; Projection to latent structures; Quantitative model; Radial basis function networks; Radial basis function networks (RBFN); Reactive batch distillation; Reactive distillation column; Recursive least squares; Sensitivity index; Sensor configuration; Sensor selection; Sensors selection; Singular value decomposition; Soft sensing; Soft sensor; Stability; State and parameter estimation; State estimation; State estimator; State space representation