SIMULINK Simulation Code for Asynchronous Motor with Current Hysteresis-Based Fuzzy PI Control

Asynchronous motors are widely used in modern industrial drive systems, where control strategies directly impact system performance. While conventional PI control offers simple structure, its regulation capability becomes limited under nonlinear operating conditions. The improved solution combining current hysteresis control with fuzzy logic significantly enhances dynamic response characteristics. The core principle of current hysteresis control involves setting upper and lower thresholds to constrain current fluctuation ranges. When actual current exceeds predefined boundaries, the controller immediately adjusts PWM signals to force rapid current recovery within permissible limits. This control method features fast response and strong robustness, particularly suitable for applications requiring quick dynamic adjustments. In code implementation, this typically involves creating hysteresis comparator blocks with configurable bandwidth parameters and real-time current monitoring functions. Fuzzy PI control adapts to system variations through online adjustment of proportional and integral parameters. Unlike traditional fixed-parameter PI controllers, fuzzy logic dynamically modifies control parameters based on current error and its rate of change, effectively resolving parameter mismatch issues during motor startup and load transient conditions. The algorithm implementation requires designing membership functions for input variables (error and error derivative) and establishing rule bases for output parameter tuning. When implementing this composite control strategy in SIMULINK environment, several key modules need construction: Current detection modules acquire three-phase motor currents using measurement blocks with sampling rate configuration; Hysteresis comparator modules perform real-time boundary violation checks through relational operators and switching logic; Fuzzy inference engine modules generate dynamic PI parameters using Fuzzy Logic Controller blocks with rule evaluation algorithms; PWM generation modules ultimately output drive signals through carrier comparison and pulse width modulation techniques. The advantage of this control strategy lies in preserving the rapid response characteristics of current hysteresis while improving system adaptability across different operating conditions through fuzzy algorithms. Simulation experiments demonstrate that compared to traditional control methods, this solution exhibits smaller overshoot and shorter settling time during motor startup and load突变 scenarios. The code structure typically organizes these modules into hierarchical subsystems with proper signal routing and parameter tuning interfaces for practical deployment.