Qualitative-evolutionary design of greenhouse environment control agents

A novel technique that fuses qualitative reasoning and evolutionary computation in the design of control agents for the control of the environment of a greenhouse is proposed in this paper. Linguistic rules relate the attributes of the greenhouse performance in response to perturbations in the desir...

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Bibliographic Details
Published in:Computers and electronics in agriculture 2000-05, Vol.26 (3), p.271-282
Main Authors: Goggos, V, King, R.E
Format: Article
Language:English
Subjects:
Agronomy. Soil science and plant productions
Biological and medical sciences
Computational intelligence
Control agents
Evolutionary computation
Fundamental and applied biological sciences. Psychology
Fuzzy inference
General agronomy. Plant production
Genetic algorithms
Hierarchical control
Protected cultivation
Soilless cultures. Protected cultivation
Stochastic search
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Summary:A novel technique that fuses qualitative reasoning and evolutionary computation in the design of control agents for the control of the environment of a greenhouse is proposed in this paper. Linguistic rules relate the attributes of the greenhouse performance in response to perturbations in the desired set points to the suitability of the agent. De-fuzzification of the fuzzy suitability membership function yields a quantitative measure of the fitness of the agent to satisfy the system performance specifications. The fitness measure is used in a genetic algorithm that performs a stochastic search for the global optimum parameters of the agent.
ISSN:0168-1699
1872-7107
DOI:10.1016/S0168-1699(00)00080-6