PERANCANGAN PENGONTROL ADAPTIF BERBASIS ALEURO FUZZY PADA DISTILASI KOLOM JENIS BUBBLE CAP KONTINYU - Shoelarta, Shoerya
Bubble cap column distillation is one of the mostwidely used separation process units. The separation is based on boiling point difference between components. Ethanol-aqua mixture is a difficult mixture to separate for achiving high purity (>95%) continously due to azeotropic property. The existing controllers for the unit in Pilot plant laboratory at Politeknik Negeri Bandung are Siemens SC 135 PID controllers which are relativelly modern, fully featured but do not quite fulfill the expectation. In this research, an Adaptive Neuro Fuzzy Inference Sytem (ANFIS) is applied by means of a hybrid learning algorithm using Error Back Propagation (EBP) and Least Square Estimator (LSE). The ANFIS learning results in a Fuzzy Inference System (FIS) matrix with 64 rules and reasonably small error of 0.004 after 40 epochs. This FIS matrix is then used as plants model, which is a function transfer as well. An inverse dynamic controller is applied consisting of a matrix of 1 input that is error and 6 outputs. The simulated closed loop will give rise relatively fine respons, which appropriate tuning of membership functions. The residual error is less than 1%, although a 3 minute settling time is inevitable. A modified controller with 2 inputs namely error and rate of error gives rise to even better responds, under 0.5 % of residual error and 3 minute settling time which are significantly better than that of existing PID controllers in real practice that are 1-2 % and 10-11 minute respectively. Altough the PID respons at 1 minute, faster than the simulated plant at 2 minutes. Key words : distillation, separation, neuro_fuzzy, inverse dynamics, error