DYNAMIC POSITIONING ℋ∞ CONTROLLER TUNING BY GENETIC ALGORITHM
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Summary
To cope with the imprecision and vagueness that arises in the description of objective functions, and constraints of the process and actuators, concepts from the fuzzy logic are incorporated into the solution.
- Type
- article
- Published
- 2002-01-01
- Cited by
- 2
- References
- 11
- OpenAlex
- https://openalex.org/W37518361
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:9572337
Keywords
Fuzzy logic, Vagueness, Genetic algorithm, Mathematical optimization, Weighting
References
- Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems
- Robust and optimal control
- Operational performance of an initial design of self-organising fuzzy logic autopilot
- Robust control of an unknown plant : the IFAC 93 benchmark
- Robust control design via eigenstructure assignment, genetic algorithms and gradient-based optimisation
- Multiobjective fuzzy genetic algorithm optimisation approach to nonlinear control system design
- Gain scheduling based fuzzy controller design
- Multiobjective fuzzy genetic algorithm optimization approach to nonlinear control system design
- Robust and Optimal Control
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