In this paper, a new radial basis function network-based model predictive control (RBFN-
MPC) is presented to control the steam temperature of a power plant boiler. For the first time …

This study presents a model predictive control of a 4× 3 Multiple-Input Multiple-Output
(MIMO) biomass control system that uses radial basis function (RBF) as an activation …

This paper introduces a new method based on intelligent model predictive control to control
the temperature of a boiler. First, several linear local models (as a transfer function) are …

This paper proposes a new factorized f-step radial basis function network (FS-RBF) model
for model predictive control (MPC). The strategy is to develop a f-step predictor for nonlinear …

A linear parameter-varying model (LPVM) is developed for nonlinear dynamic systems using
a radial basis function (RBF) neural network. The training of the LPVM is formulated as the …

A robust model predictive control (MPC) with bi-level optimization is proposed for nonlinear
boiler-turbine system. The nonlinear dynamics are described by multiple local models …

A novel neural architecture for prediction in industrial control: the'Double Recurrent Radial
Basis Function network'(R2RBF) is introduced for dynamic monitoring and prognosis of …

The ultra supercritical (USC) for the boiler-turbine unit has become an advanced power
generation technology due to its high combustion efficiency and low-carbon emission …

In this paper, a neural network based controller is applied to a heat exchanger pilot plant.
The dynamics of the plant is identified using an MLP neural network. Then, the predictive …

The circulating fluidized bed boiler (CFBB) generator has following characteristics: multi-
variable, non-linear, strong coupling, time-varying characteristics. The combustion is still in …