In this work, a novel model predictive control (MPC) scheme is introduced, by integrating direct and indirect neural control methodologies. The proposed approach makes use of a …
S Guo, D Liu, X Chen, Y Chu, C Xu, Q Liu, L Zhou - Applied energy, 2017 - Elsevier
This work describes and evaluates a new nonlinear dynamic model, and a new generalized predictive control scheme for a collector field of direct steam generation parabolic troughs in …
H El Fadil, F Giri - Control Engineering Practice, 2011 - Elsevier
The problem of maximum power point tracking (MPPT) is addressed for photovoltaic (PV) arrays considered in a given panel position. The PV system includes a PV panel, a PWM …
H Han, W Zhou, J Qiao, G Feng - IEEE Transactions on Neural …, 2015 - ieeexplore.ieee.org
This paper is concerned with the problem of adaptive neural control for a class of uncertain or ill-defined nonaffine nonlinear systems. Using a self-organizing radial basis function …
M Pasamontes, JD Álvarez, JL Guzmán… - Control Engineering …, 2011 - Elsevier
This work presents a new switching control procedure that has been chosen to deal with the changes in plant dynamics. Several control systems composed of IMC-based PID controllers …
This paper aims at the proposition of novel architectures for radial basis function neural networks implementation on hardware with custom-precision floating-point operations for …
This article presents the theoretical and experimental performance of a Solar Cavity Receiver (SCR) which operates under controlled conditions of radiation and flow regulation …
The exact output regulation problem for Takagi‐Sugeno (TS) fuzzy models, designed from linear local subsystems, may have a solution if input matrices are the same for every local …