Authors:
Ernesto Ponce
;
Claudio Ponce
and
Bernardo Barraza
Affiliation:
Tarapacá University, Chile
Keyword(s):
Neural Network, Spirulina, Control, Aquaculture, Signal Processing System.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Expert Systems
;
Health Information Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Neural Networks Based Control Systems
;
Symbolic Systems
Abstract:
A neural network that was designed to control a Spirulina aquaculture process in a pilot plant in the north of Chile, is presented in this work. Spirulina is a super food, but is a delicate alga and its culture may be suddenly lost by rapid changes in the weather that can affect its temperature, salinity or pH. The neural network control system presented is complex and non linear, and has several variables. The previous automatic control system for the plant proved unable to cope with large climatic variations. The advantage of this new method is the improvement in efficiency of the process, and a reliable control system that is able to adapt to climatic changes. The future application of this work is related to the industrial production of food and fuel from micro algae culture, for the growing world population.