Trajectory tracking of a batch polymerization reactor based on input-output-linearization of a neural process model

Computers and Chemical Engineering

Volumn 25, Issue 11-12, 2001, Pages 1561-1567

  Horn, Joachim ^a  

^a SIEMENS AG   (Germany)

Author keywords

Batch reactor; Data based modeling of dynamic systems; Input output linearization; Neural process model; Trajectory tracking

Indexed keywords

COST EFFECTIVENESS; FEEDBACK; NEURAL NETWORKS; POLYMERIZATION;

TRAJECTORY TRACKING;

CHEMICAL ENGINEERING;

BATCH PROCESS; POLYMERIZATION; REACTOR;

ARTICLE; ARTIFICIAL NEURAL NETWORK; COST; DYNAMICS; FEEDBACK SYSTEM; INTERMETHOD COMPARISON; LINEAR SYSTEM; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; NONLINEAR SYSTEM; POLYMERIZATION; TIME;

EID: 0035890801     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0098-1354(01)00719-0     Document Type: Article

References (16)

1. Control of batch reactors: A review
2. Asymptotically exact I/O-linearization of an industrial distillation column
3. Degree of approximation results for feedforward networks approximating unknown mappings and their derivatives
4. Nonlinear state feedback synthesis by global input/output linearization
5. Identification and control of dynamical systems using neural networks
6. Globally linearising control using artificial neural networks
7. Adaptive control of linearizable systems
8. Robust input-output feedback linearization
9. Nonlinear control of a batch polymerization reactor: An experimental study
10. Optimal design and operation of batch reactors. 2. A case study
11. Neural modeling of nonlinear differential equations with discrete measurements - A Lagrangian approach
12. Adaptation of dynamic process models with integral data - A Lagrangian approach
13. Dynamic modeling of chemical reaction systems with neural networks and hybrid models