The method of automatic synthesis of a fuzzy controller and optimization of its parameters based on a genetic algorithm is developed. A distinctive feature of the method is an algorithm for processing statistical data about the operation of a real industrial facility, which makes it possible to form the initial knowledge base of a fuzzy controller (the number and type of membership functions used, the base of control rules). The use of a genetic algorithm allows optimizing the parameters of a fuzzy controller in such a way as to ensure the best quality indicators of its operation: the duration and oscillation of the transient process, the value of the steady-state error. The proposed method is automated due to the development of a special software application in the Matlab modeling environment, and requires minimal human participation in its work. Simulation modeling is carried out and results are presented that confirm the correctness of the proposed method and the possibility of its practical use. The method operation can be represented as a sequence of the following stages: forming the initial parameters of a fuzzy controller; searching for optimal lengths of term-sets of input-output linguistic variables; searching for optimal parameters of term-sets of input–output linguistic variables.
The article presents a comparison of a few controllers of the vessel's course. The mathematical model of the vessel was set as a transfer function with variable coefficients, which depend on vessel speed. We compared a classic PID controller, a PID controller with self-adjusting coefficients, an adaptive controller with implicit reference model, and an adaptive fuzzy controller. In the result of comparison the adaptive fuzzy controller demonstrated the best quality indicators in comparison with other controllers by set of criteria that allows to recommend this controller for implementation in the vessel's course control systems.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.