The FLC for swing-up brings the pendulum near to its inverted position from downward position between 5 and 10 seconds. The FLC for stabilization maintains the pendulum near to inverted position with average ±1 degree of error and the cart near to zero position with average ±0.02 m of error.
In this study, a real-time control of the cart-pole inverted pendulum system was developed using fuzzy logic controller. Swing-up and stabilization of the ...
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In this study, a real-time control of the cart-pole inverted pendulum system was developed using fuzzy logic controller (FLC). Swing-up and stabilization of the ...
In this study, a real-time control of the cart-pole inverted pendulum system was developed using fuzzy logic controller (FLC). Swing-up and stabilization of ...
Abstract. In this study, a real-time control of the cart-pole inverted pendulum system was developed using fuzzy logic controller.
The basic aim of our work was to balance a real pendulum in the position in center of course. For this purpose we used fuzzy logic controller. The fuzzy logic ...
In this paper, a data-driven Takagi-Sugeno fuzzy model called. ANFIS is employed for the stabilizing control, and a semi- physical simulation test system for ...
Abstract. In this study, a real-time control of the cart-pole inverted pendulum system was developed using fuzzy logic controller.
In this paper, a fuzzy controller for an inverted pendulum system is presented in two stages. These stages are: investigation of fuzzy control system modeling ...
This document is dedicated to explaining briefly how the Fractional Fuzzy Inference Systems (FFISs) can be implemented in MATLAB through the use of the ...
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