Stabilization control of series-type double inverted pendulum systems using the SIRMs dynamically connected fuzzy inference model

2001 ◽  
Vol 15 (3) ◽  
pp. 297-308 ◽  
Author(s):  
Jianqiang Yi ◽  
Naoyoshi Yubazaki ◽  
Kaoru Hirota
Keyword(s):  
Inverted Pendulum ◽  
Fuzzy Inference ◽  
Inference Model ◽  
Stabilization Control ◽  
Series Type

A New Fuzzy Controller for Stabilizing Inverted Pendulums Based on Single Input Rule Modules Dynamically Connected Fuzzy Inference Model

2001 ◽  
Vol 5 (1) ◽  
pp. 58-70 ◽  
Author(s):  
Jianqiang Yi ◽  
◽  
Naoyoshi Yubazaki ◽  
Kaoru Hirota ◽  
◽  
...  
Keyword(s):  
Position Control ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Initial Position ◽  
Initial Angle ◽  
Inference Model ◽  
Stabilization Control ◽  
Control Situations ◽  
Single Input ◽  
Simulation Results

A fuzzy controller is presented based on the Single Input Rule Modules (SIRMs) dynamically connected fuzzy inference model for stabilization control of inverted pendulums. The angle and angular velocity of the pendulum and the position and velocity of the cart are selected as input items and the driving force as the output item. By using SIRMs and dynamic importance degrees, the fuzzy controller realizes angular control of the pendulum and position control of the cart in parallel with totally only 24 fuzzy rules. Switching between angular control of the pendulum and position control of the cart is smoothly performed by automatically adjusting dynamic importance degrees according to control situations. For any inverted pendulums, of which the pendulum length is among [0.5m, 2.2m], simulation results show that the proposed fuzzy controller has a high generalization ability to stabilize the pendulum systems completely in about 6.0 seconds when the initial angle of the pendulum is among [-30.0°, +30.0°], or the initial position of the cart is among [-2.1m, +2.1m].

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