Abstract
A robust adaptive Sugeno based fuzzy sliding mode controller equipped with a supervisory controller is considered for the control of nonlinear systems which significantly reduce computation via reducing the size of fuzzy rule base. Besides, all the system parameters such as control and state signals can be confined to a predefined bounded region by use of proposed control method. Also the proposed method does not need any information of the controlled plant. Tracking and regulation simulations on an inverted pendulum system highlights that the proposed method is superior than the classical Sugeno based fuzzy controllers for the control of ill-defined nonlinear systems.
Keywords
Control theory (sociology)
Sliding mode control
Nonlinear system
Fuzzy logic
Controller (irrigation)
Inverted pendulum
Fuzzy control system
Computer science
Robustness (evolution)
Robust control
Adaptive control
Adaptive neuro fuzzy inference system
Control engineering
Engineering
Control (management)
Artificial intelligence
Subject Areas
Adaptive Control of Nonlinear Systems
·Control and Systems Engineering ·Physical Sciences
Fuzzy Logic and Control Systems
·Artificial Intelligence ·Physical Sciences
Advanced Control Systems Design
·Control and Systems Engineering ·Physical Sciences
Citations by Year
2013: 1
OpenAlex SDG Match
SDGs auto-classified by OpenAlex (score ≥ 0.4 shown).
Affordable and clean energy 54%
Loading…
Loading…