Experimental Studies of Swing Up and Balancing Control of an Inverted Pendulum System Using Intelligent Algorithms Aimed at Advanced Control Education

Abstract

This paper presents the control of an inverted pendulum system using intelligent algorithms, such as fuzzy logic and neural networks, for advanced control education. The swing up balancing control of the inverted pendulum system was performed using fuzzy logic. Because the switching time from swing to standing motion is important for successful balancing, the fuzzy control method was employed to regulate the energy associated with the angular velocity required for the pendulum to be in an upright position. When the inverted pendulum arrived within a range of angles found experimentally, the control was switched from fuzzy to proportional-integral-derivative control to balance the inverted pendulum. When the pendulum was balancing, a joystick was used to command the desired position for the pendulum to follow. Experimental results demonstrated the performance of the two intelligent control methods.

Robust Control for the Segway with Unknown Control Coefficient and Model Uncertainties

“…It is well known that the backstepping technique requires the differentiation of the virtual control and this complicates the controller. Although the dynamic surface control method [ 8 ] can remove the disadvantage of the backstepping technique, it is still complex because it should use the adaptive technique [ 9 , 10 ], neural network [ 11 , 12 , 13 ], and fuzzy logic [ 14 , 15 ] to deal with the uncertainties.…”