Open AccessReal- time implementation of parallel type fuzzy- PID controller for effective control of hybrid Pole self bearing Switched reluctance motor
Author(s) -
R. Subramanyam Naidu,
U. Salma
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.21.11847
Subject(s) - pid controller , control theory (sociology) , fuzzy logic , controller (irrigation) , computer science , control engineering , open loop controller , matlab , fuzzy control system , control system , engineering , temperature control , control (management) , artificial intelligence , agronomy , electrical engineering , closed loop , biology , operating system
This paper presents a hybrid intelligent and design in a real time for the rapid prototyping of a robust fuzzy controller along with conventional Proportional– Integral and Derivative (PID) controller that allows quick insight of these integrated designs. The design procedure of the parallel fuzzy PID and its combination with the traditional PID in a universal control scheme are extended. The structural design of the parallel fuzzy PID controller is composed of three fuzzy sub controllers which are connected in parallel. These parallel sub controllers are assembled to get the proposed parallel fuzzy type PID controller. The hybrid fuzzy PID gains are expressed in the error domain. Hence, the structural design presents an alternative to control schemes employed so far. This hybrid intelligent controller is formulated and executed in real world hardware for position as well as speed control of a Hybrid Pole Self Bearing Switched Reluctance Motor (HPSBSRM) drive system. The design of the parallel fuzzy PID controller, implementation and finally analysis all are carried out using MATLAB/Simulink environment. Software results concluded that the novel hybrid intelligent parallel fuzzy PID controller generates better control action when compared to traditional PID controller, predominantly in system nonlinearities and in external load variations.