Bio-Inspired PSO Optimization of Fuzzy Membership Boundaries and PI Gains for a 48 V Synchronous Boost Converter

Abstract

48 V bus modules must stay regulated under wide input-voltage swings and fast load transients. A proportional-integral (PI) controller and a fuzzy logic controller (FLC) are tuned by the same Particle Swarm Optimization (PSO), a swarm metaheuristic modeled on bird-flock foraging, under an Integral of Time-weighted Absolute Error (ITAE) objective. The novelty is PSO-based membership-boundary optimization: the membership-function limits, analogues of biological decision thresholds, are shaped directly rather than only the scaling gains. A 153 W, 225 kHz synchronous boost converter is simulated with non-ideal parasitics. For input-voltage transitions the PSO-FLC shortens settling time by up to 70.5% (118 versus 400 ms), whereas the PSO-PI gives smaller peak deviation (26.2% versus 40.0%) and faster load-step recovery. Unconstrained, both controllers draw 58–62 A on the worst input-voltage step; a 10 A cycle-by-cycle limit removes these excursions. Under an identical budget and parameter count, boundary tuning attains 12.3% lower ITAE cost and roughly 40% shorter large-signal settling than scaling-gain tuning. Across ten runs the cost varies by under 1.5% of its mean, and the ranking holds at a realizable update rate (4.44 μs, zero-order hold) and under the current limit. The findings are simulation-only comparative design guidance.