Open AccessDecoupling Fuzzy-Neural PID Controller for TITO Nonlinear Systems
Author(s) -
Иван Ганчев,
Sevil Ahmed,
Albena Taneva,
Michail Petrov
Publication year - 2016
Publication title -
information technologies and control
Language(s) - English
Resource type - Journals
eISSN - 2367-5357
pISSN - 1312-2622
DOI - 10.1515/itc-2017-0002
Subject(s) - decoupling (probability) , control theory (sociology) , pid controller , nonlinear system , fuzzy logic , control engineering , benchmark (surveying) , computer science , engineering , control (management) , artificial intelligence , temperature control , physics , quantum mechanics , geodesy , geography
This paper presents a fuzzy-neural structure of a Decoupling Fuzzy PID controller with self-tuning parameters. This structure is appropriate for Two-Input-Two-Output (TITO) nonlinear system. The main advantage here is that the equation of classical PID control and decoupling coefficients are used as a Sugeno function into the fuzzy rules. Hence the designed decoupling fuzzy PID controller can be viewed as a natural similarity to the conventional one with decoupling elements. A benchmark quadruple tank, implementing a TITO nonlinear system is considered to illustrate the benefits of the design paradigm. The performance of this set up was studied for reference tracking and disturbance rejection cases. Simulation results confirm the effectiveness of the proposed solution.