Study on Fuzzy PID control with an improved genetic algorithm for boiler drum water level

Abstract Stable control of boiler drum water level is a core component in ensuring industrial production efficiency and operational safety. However, traditional fuzzy proportional-integral-derivative (PID) controllers suffer from deficiencies such as inadequate dynamic performance and weak interference resistance, making them ill-suited for complex operational conditions; while PID controllers optimized using conventional genetic algorithms (GA) can improve certain performance metrics, they often fall into the trap of ‘over-optimizing a single metric at the expense of overall performance balance’ (such as reducing regulation time while causing overshoot), and their convergence speed remains suboptimal. To address these issues, this paper proposes an Improved Genetic Algorithm (IGA)-optimized Fuzzy PID controller (IGA-Fuzzy PID), which integrates the advantages of Fuzzy Logic Control (FLC) and IGA to achieve synergistic optimization of the system’s overall performance. To validate its effectiveness, simulation experiments were conducted on the proposed IGA-Fuzzy PID controller, combined with Bode plot analysis to assess system stability, and compared with traditional Fuzzy PID and GA-optimized Fuzzy PID controllers. The results demonstrate that the IGA-Fuzzy PID controller exhibits significant advantages in optimizing overall system performance, achieving rapid disturbance response, and ensuring stable recovery.