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송정준(Jeong Jun Song),박선원(Sunwon Park) 대한전자공학회 1992 대한전자공학회 학술대회 Vol.1992 No.10
A neural model predictive control strategy combining a neural network for plant identification and a nonlinear programming algorithm for solving nonlinear control problems is proposed. A constrained nonlinear optimization approach using successive quadratic programming cooperates with neural identification network is used to generate the optimum control law for the complicate continuous / batch chemical reactor systems that have inherent nonlinear dynamics. Based on our approach, we developed a neural model predictive controller (NMPC) which shows excellent performances on nonlinear, model-plant mismatch cases of chemical reactor systems.
Time-Delay Neural Network를 이용한 중류탑의 on-line 고장 진단
이상규(Sanggyu Lee),박선원(Sunwon Park) 대한전자공학회 1992 대한전자공학회 학술대회 Vol.1992 No.10
Modem chemical processes are becoming more complicated. The sophisticated chemical processes have needed the fault diagnosis expert systems that can detect and diagnose the faults of some processes and give an advice to the operator in the event of process faults. We present the Time-Delay Neural Network (TDNN) approach for on-line fault diagnosis. The on-line fault diagnosis system finds the exact origin of the fault of which the symptom is propagated continuously with time. The proposed method has been applied to a pilot distillation column to show the merits and applicability of the TDNN.