Fuzzy Control Simulation of Double Inverted Pendulum Using Simulink

This research conducts simulation studies on double inverted pendulum systems using Simulink for fuzzy control experiments to explore control effectiveness and system stability. By designing appropriate control strategies, precise control and stability improvement of the inverted pendulum system can be achieved. Fuzzy control represents a highly promising control methodology applicable to various complex systems, including inverted pendulum configurations. In our fuzzy control simulation experiments, we utilize Simulink to construct a comprehensive simulation model of the double inverted pendulum system, implementing fuzzy logic controllers to regulate its dynamic behavior. The implementation involves designing fuzzy inference systems using Mamdani or Sugeno methods, where membership functions for input variables (such as angle and angular velocity) and output control signals are carefully defined. Through systematic adjustment and optimization of fuzzy controller parameters - including rule base refinement, membership function tuning, and defuzzification methods - we can significantly enhance the control performance of the inverted pendulum system, achieving greater stability and precision. Key implementation aspects include: - Designing fuzzy logic controller blocks in Simulink using Fuzzy Logic Toolbox - Establishing appropriate fuzzy rules based on system dynamics - Tuning membership functions for optimal response - Implementing real-time control algorithms for stability maintenance This research provides valuable insights into control theories and methodologies for double inverted pendulum systems, offering practical references for applications in related fields such as robotics, aerospace engineering, and industrial automation systems.