OPTIMASI PARAMETER PENGENDALI IMC-PI/PID BERBASIS ALGORITMA GENETIKA UNTUK SISTEM FOPDT DAN SOPDT DENGAN DEAD TIME
DOI:
https://doi.org/10.53026/prosidingsntem.v5i1.742Keywords:
Internal Model Control, Algoritma Genetika, Dead Time, RobustnessAbstract
Fenomena dead time pada sistem proses industri menyebabkan penurunan kinerja pengendali dan sensitivitas terhadap ketidakpastian model. Penelitian ini mengintegrasikan Internal Model Control (IMC) dengan Algoritma Genetika (GA) untuk mengoptimasi parameter pengendali PI/PID pada model FOPDT dan SOPDT dengan dead time. Model proses FOPDT menggunakan parameter K=2, τ=300s, θ=40s, sedangkan SOPDT dengan K=1,5, τ₁=200s, τ₂=800s, θ=60s. Parameter GA divariasikan pada ukuran populasi 30-250, generasi 50-500, probabilitas crossover 0,8-1,0, dan mutasi 0,2-0,5, dengan fungsi objektif ITAE yang meminimalkan error kumulatif, overshoot, dan saturasi aktuator. Hasil optimasi menunjukkan penurunan ITAE sebesar 50-72% dibandingkan tuning manual, overshoot tereduksi menjadi 12,48% (FOPDT) dan 0,23% (SOPDT), serta eliminasi saturasi aktuator. Uji robustness dengan variasi dead time ±30% dan mismatch parameter ±20% membuktikan sistem mempertahankan stabilitas dengan degradasi kinerja maksimal 17,9%. Metrik Relative Delay Margin (RDM) 0,48-0,52 dan Maximum Sensitivity (Ms) 1,38-1,42 mengonfirmasi ketahanan pengendali terhadap ketidakpastian model, menjadikan metode ini solusi efektif untuk kontrol temperatur industri kilang.
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