FUZZY LOGIC CONTROLLER FOR INVERTED PENDULUM WITH REDUCED LINGUISTIC VARIABLE

Abstract

The inverted pendulum is a classical control problem, which involves developing a control system to balance a pendulum. The aim of this study is to stabilize the Inverted Pendulum such that the position of the cart on the track is controlled quickly and accurately so that the pendulum is always erected in its inverted position during such movements. This thesis present a design methodology for stabilization of an IP (Inverted Pendulum) with reference tracking using ANFIS (Adaptive Neural Fuzzy Inference System) with a single linguistic variable and two membership function only hence two rules. The proposed FLC (Fuzzy Logic Controller) is the simplest FLC that retains all the merits of four input linguistic variable FIS tuned by ANFIS and is more robust than the conventional PD controller. Experiments are carried out in MATLAB Simulink to demonstrate the performance of the purposed controller. The design procedure is conceptually simple and natural. In this design procedure firstly two independent PD controllers are tuned one for angle and another for cart position on the rail. Now training data is taken from these controllers and FIS is tuned with the help of ANFIS. Once FIS is tuned, then further work is carried out to reduce the numbers of input linguistic variables, by adding one variable to another and tuning the gain parameters using trial and error method. Systems are simulated in the presence of disturbance. Overshoot and settling time are also kept in mind while comparing between two simulation results, because these two entities are mutually dependent on each other, if we reduce one the other will increase, and vice-versa. iii