Robust Stability Self-Tuning Fuzzy PID Digital Controller

Robust Stability Self-Tuning Fuzzy PID Digital Controller

Ginalber Luiz de Oliveira Serra (Federal Institute of Education, Science and Technology, Brazil) and Edson B. M. Costa (IFMA, Brazil)
DOI: 10.4018/978-1-5225-3129-6.ch006
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Abstract

A self-tuning fuzzy control methodology via particle swarm optimization based on robust stability criterion, is proposed. The plant to be controlled is modeled considering a Takagi-Sugeno (TS) fuzzy structure from input-output experimental data, by using the fuzzy C-Means clustering algorithm (antecedent parameters estimation) and weighted recursive least squares (WRLS) algorithm (consequent parameters estimation), respectively. An adaptation mechanism based on particle swarm optimization is used to tune recursively the parameters of a fuzzy PID controller, from the gain and phase margins specifications. Computational results for adaptive fuzzy control of a thermal plant with time varying delay is presented to illustrate the efficiency and applicability of the proposed methodology.
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Background

The pioneer researches in adaptive control occurred in the early 1950s motivated mainly by the design of autopilots for high-performance aircraft. The main complexities in such projects are the wide range of speeds and altitudes that the aircraft operates, nonlinear dynamics and time varying characteristics. Primary results on adaptive flight control are given in Gregory (1959), Mishkin and Braun (1961) and Whitaker et al. (1958). Although these works were successful, the lack of concise theoretical framework and a disaster in a flight test diminished the interest in the area (Taylor and Adkins, 1965).

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