Smarter Temperature Control Could Make Industrial Machines Faster and Safer
Better temperature control means higher-quality products and less wasted energy.
Temperature control is critical in industrial automation, but traditional PID and manual fuzzy controllers often struggle with delays and system drift. This article presents a fuzzy PID strategy optimized by a Levy-flight Improved Particle Swarm Optimization algorithm, designed to escape premature convergence and boost efficiency. Tested on a simulated first-order plus dead time model, the method cut settling time to 105.5 seconds—about 46.7% faster than standard PSO and 42.5% faster than other improved PSO variants—while reaching an optimal ITAE value. Robustness tests also confirmed superior stability under severe model mismatches, showing strong promise for high-precision industrial applications.