Orthogonal spline collocation methods for partial differential equations
Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 Vol. VII: partial differential equations
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural Networks - 2003 Special issue: Advances in neural networks research IJCNN'03
Adaptive recurrent neural network control of biological wastewater treatment: Research Articles
International Journal of Intelligent Systems - Soft Computing for Modeling, Simulation, and Control of Nonlinear Dynamical Systems
Diagrammatic derivation of gradient algorithms for neural networks
Neural Computation
Adaptive-critic based optimal neuro control synthesis for distributed parameter systems
Automatica (Journal of IFAC)
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The paper proposed to use a Recurrent Neural Network Model (RNNM) and a dynamic Backpropagation learning for centralized identification of an anaerobic digestion bioprocess, carried out in a fixed bed and a recirculation tank of a wastewater treatment system. The anaerobic digestion bioprocess represented a distributed parameter system, described by partial differential equations. The analytical model is simplified to a lumped ordinary system using the orthogonal collocation method, applied in three collocation points, generating data for the neural identification. The obtained neural state and parameter estimations are used to design an indirect sliding mode control of the plant. The graphical simulation results of the digestion wastewater treatment indirect control exhibited a good convergence and precise reference tracking.