State-space neural network for modelling, prediction and control

Control Engineering Practice

Volumn 8, Issue 9, 2000, Pages 1063-1075

  Zamarreno J M ^a   Vega, P ^b   Garcia L D ^b   Francisco, M ^b  

^a UNIVERSITY OF VALLADOLID   (Spain)

^b UNIVERSITY OF SALAMANCA   (Spain)

Author keywords

Control; Modelling; Neural networks; Prediction; State space

Indexed keywords

INDUSTRIAL APPLICATIONS; MATHEMATICAL MODELS; NEURAL NETWORKS; PROCESS CONTROL; STATE SPACE METHODS; SUGAR MANUFACTURE;

CONTROL ENGINEERING;

PREDICTIVE CONTROL SYSTEMS;

CONTROL; MODELING; NEURAL NETWORK; PREDICTION;

EID: 0034283424     PISSN: 09670661     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0967-0661(00)00045-9     Document Type: Article

References (10)

1. Multilayer feed forward networks are universal approximators
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3. Identification, simulation and optimal control of the diffuser process in the sugar industry
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5. Model predictive heuristic control: Applications to industrial processes
6. 30 years of adaptive neural networks: Perceptron, madaline, and backpropagation
7. Identification and predictive control of a melter unit used in the sugar industry
8. State space neural network
9. Neural predictive control. Application to a highly non-linear system