Self-tuning control of steam sterilizer temperature based on fuzzy PID and IPSO algorithm

Abstract

A time-varying process with nonlinearity and time lag is the temperature control of pulsing vacuum steam sterilization. In order to achieve efficient and accurate control requirements, conventional PID temperature control algorithms sometimes display slow response speed, severe overshooting, unstable performance, and other challenges that ultimately affect the sterilizing effect. In order to find the ideal steam sterilization temperature control settings iteratively, this research used the PSO algorithm. Simulating and analyzing the system model is done simultaneously using fuzzy control of the PID parameter adaptive modification. According to the results, there is no overshooting and the response speed approach is faster. This paper presents an approach to fuzzy PID control based on the PSO optimization algorithm. As a result of fuzzy adaptive PID's high control accuracy and quick response time, the PID parameters are also continuously optimized utilizing the PSO approach for steam sterilization temperature control. For the purpose of doing simulation analysis, create and modify a system model. As evidenced by the results, this strategy has a reduced overshoot, a faster response time, and better stability. It may also successfully boost the control effect. Eventually, this method was applied to a self-tuning PID control experiment for sterilizer temperature control, and a relatively optimal control effect was obtained.