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Conventional fuzzy control and its enhancement.
1Control Lab., Auckland Univ.
Summary
This study introduces a robust fuzzy control design, simplifying tuning by focusing on scaling gains. Enhanced fuzzy three-term controllers improve performance, validated through simulations on various models.
Area of Science:
- Control Engineering
- Automation Systems
- Computational Intelligence
Background:
- Conventional fuzzy control methods, including fuzzy two-term and fuzzy three-term control, present design and tuning challenges.
- Digital implementation of fuzzy control is crucial to mitigate sampling time influences.
Purpose of the Study:
- To provide a more systematic analysis and design framework for conventional fuzzy control.
- To develop a simplified and enhanced fuzzy three-term controller for improved performance.
- To present effective tuning strategies for fuzzy control systems.
Main Methods:
- Proposing a general robust rule base for fuzzy two-term control, optimizing through scaling gains.
- Presenting digital implementation techniques for fuzzy controllers.
- Developing a simplified fuzzy three-term controller based on prior fuzzy two-term controller results.
- Introducing a two-level tuning strategy for fuzzy proportional/integral/derivative (PID) gains and control resolution.
Main Results:
- The proposed robust rule base for fuzzy two-term control simplifies design and tuning.
- Digital implementation effectively addresses sampling time issues in fuzzy control.
- The simplified fuzzy three-term controller demonstrates enhanced performance.
- Simulations across various model orders validate the new design methodologies and the advantages of the enhanced fuzzy three-term control.
Conclusions:
- The presented methodologies offer a systematic approach to fuzzy control design and tuning.
- The enhanced fuzzy three-term controller provides superior performance compared to conventional methods.
- The study highlights the practical applicability and effectiveness of the proposed fuzzy control strategies.
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