Análise multinível wavelet como fitness na sintonia de controladores utilizando meta-heurísticas
The control of dynamic systems is a challenge, the methods traditionally used in tuning present the difficulty in expressing the desired specifications and being able to find controllers that produce these requirements, especially when the case requires more complex controllers, as in the case of...
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| Formato: | Dissertação |
| Idioma: | por |
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| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/24829 |
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| Resumo: | The control of dynamic systems is a challenge, the methods traditionally used in tuning
present the difficulty in expressing the desired specifications and being able to find
controllers that produce these requirements, especially when the case requires more complex
controllers, as in the case of Multiple Input Multiple Output (MIMO) problems. Due
to the increasing competitiveness in the industry, it becomes imperative to use more efficient
tuning techniques and that in fact can find controllers with the desired performance.
For this, one can use metaheuristics, such as Particle Swarm Optimization (PSO), Genetic
Algorithm (AG) and Vagalume Algorithm (AV) to obtain the parameters of the controller
according to a fitness function, which should in fact code how good a given controller is,
adequately expressing the desired specifications, so that the metaheuristic employed can
find the optimal controller, which best satisfies the chosen fitness function. Therefore, it is
proposed to use the multilevel wavelet analysis, already present in the literature, focused
on other applications, especially in the analysis of signals, sounds and images, for the creation
of an index to be used as a fitness function in control optimization. Wavelet analysis
allows to capture information on the behavior and shape of the signal by informing the
frequency of a signal over time, a characteristic that may be desirable, in the evaluation
and design of controllers and, thus, it is possible to separately evaluate the transient and
steady-state performances. A case study will be done, finding control of a MIMO system
of four coupled tanks. A comparative study was made with other fitness functions
presented in the literature and with the LGR (Geometric Place of Roots) method. The
implemented controllers presented the expected performance, and the one found using
the proposed index presented better performance. |
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