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A recurrent neural network-based nonlinear model predictive control (NMPC) scheme in parallel with PI control loops is developed for a simulation model of an industrial-scale five-stage evaporator. Input–output data from system identification experiments are used in training the network using the Levenberg–Marquardt algorithm with automatic differentiation. The same optimization algorithm is used...
This paper provides an overview of a fast modeling approach for modeling the nonlinear IO buffers for signal integrity based simulation and design of high-speed electronic interconnect and packages. Techniques based on artificial neural network (ANN) modeling are developed, where the neural network is trained to learn from IO buffer data, and trained neural network becomes fast models representing...
The use of multistage evaporators, motivated by the energy economy from reusing the flashed steam is common in a wide range of process industries. Such evaporators however present several control problems which manifest in the form of strong interactions among the many process variables, significant dead times, tendency to open-loop instability and severe nonlinearities. In this paper, a nonlinear...
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