Adaptive fuzzy sliding mode controller for a single-stage inverted pendulum

Sliding mode controller (SMC) has become a popular traditional control method in industries due to the most effective control strategies employing nonlinear control and the ability to reject disturbances, particularly for line trajectory control. However, this control method has chattering problems due to high-frequency switching. To cope with the shortcoming, an artificial intelligence (AI) method is utilized in the traditional SMC to eliminate or reduce this chattering problem. This paper investigates an adaptive fuzzy logic system combined with SMC algorithm to alleviate the problem. Fuzzy logic is chosen due to its advantages in tackling nonlinear properties using if-then thinking, whereas SMC method can be applied due to its ability to reject disturbance control. The inverted pendulum is selected as a controlled object and simulated using MATLAB/Simulink to investigate this control method. By combining the fuzzy logic system and the SMC approach, the chattering problems can be adaptively reduced on the line trajectory tracking signal. The adaptive fuzzy SMC achieved better performance with fast response compared with previous literature algorithms for similar plants.