[PDF][PDF] Nonlinear identification of pH processes by using NNARX model
M Rajalakshmi, G Saravanakumar… - Proceedings of the …, 2012 - researchgate.net
M Rajalakshmi, G Saravanakumar, C Karthik
Proceedings of the International Conference on Computing and Control …, 2012•researchgate.netNetwork Auto-Regressive model with eXogenous inputs (NNARX) in the area of
identification of nonlinear dynamical systems. The main contribution of this paper is to
identify suitable model and model structure of nonlinear dynamic system. In this paper
Neural Network Auto-Regressive model with eXogenous inputs (NNARX) and ANFIS
models are applied to identify highly nonlinear dynamic process and comparison was made
between NNARX and ANFIS. The simulation results show that ANFIS is very effective to …
identification of nonlinear dynamical systems. The main contribution of this paper is to
identify suitable model and model structure of nonlinear dynamic system. In this paper
Neural Network Auto-Regressive model with eXogenous inputs (NNARX) and ANFIS
models are applied to identify highly nonlinear dynamic process and comparison was made
between NNARX and ANFIS. The simulation results show that ANFIS is very effective to …
Network Auto-Regressive model with eXogenous inputs (NNARX) in the area of identification of nonlinear dynamical systems. The main contribution of this paper is to identify suitable model and model structure of nonlinear dynamic system. In this paper Neural Network Auto-Regressive model with eXogenous inputs (NNARX) and ANFIS models are applied to identify highly nonlinear dynamic process and comparison was made between NNARX and ANFIS. The simulation results show that ANFIS is very effective to identify the nonlinear system.
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