Fuzzy Control and Neural Network Control for Single Inverted Pendulum Systems

This paper presents fuzzy control and neural network control methodologies for single inverted pendulum systems. First, we model and simulate both control approaches within the Simulink simulation environment. When implementing fuzzy control, users must import the *.fis file into the MATLAB workspace using commands like fis = readfis('filename.fis') to load the fuzzy inference system, otherwise the controller will fail to initialize. We analyze the performance characteristics of both control methods and their applicability under different operating conditions. Specifically, we investigate their robustness against noise, external disturbances, and nonlinear system dynamics. The implementation involves designing membership functions for fuzzy controllers and configuring neural network architectures (e.g., number of hidden layers, activation functions) for effective pendulum stabilization. Finally, we discuss practical application scenarios for these control methods in real-world systems and potential enhancements for improving their performance metrics and robustness properties.