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This paper presents the empirical modeling of the gaseous pilot plant which is a kind of interacting series process with presence of nonlinearities. In this study, the discrete-time identification approach based on subspace method with N4SID algorithm is applied to construct the state space model around a given operating point, by probing the system in open-loop with variation of input signals. Three...
This study focuses on pressure control in gaseous pilot plant using model predictive control (MPC) algorithm which consists of multi-input and measurement noise. The applicated MPC uses linear approximation. Process model is obtained from subspace system identification method with amplitude modulation pseudo random binary signal (APRBS) inputs, and its control law is derived from constrained optimization...
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