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Model-Free Predictive Current Control of a Voltage Source Inverter
(Institute of Electrical and Electronics Engineers, 2020-11)
Conventional model predictive control (MPC) of power converter has been widely applied to power inverters achieving high performance, fast dynamic response, and accurate transient control of power converter. However, the ...
Design of a supervisory predictive controller based on fuzzy models
(IEEE, 2001)
In this paper, a supervisory optimal control problem is presented. Fuzzy modelling is used to represent the non-linearity of the process and two alternative fuzzy predictors are described in order to solve the optimisation ...
Predictive Control of the mineral particle size with kernel-reduced volterra models in a balls mill grinding circuit
(Institute of Electrical and Electronics Engineers Inc., 2015-06)
We report the results of the application of the Model-based Predictive Control (MPC) algorithm for a 3×3 MIMO balls mill grinding system by using computational simulation and Monte Carlo data generation. For this purpose, ...
Time Series Decomposition using Automatic Learning Techniques for Predictive Models
(Institute of Physics Publishing, 2020-01-07)
This paper proposes an innovative way to address real cases of production prediction. This approach consists in the decomposition of original time series into time sub-series according to a group of factors in order to ...
Neural network model for maximum ozone concentration prediction
(1996)
A neural network dynamic model was used for predicting maximum ozone (O3) concentration at Santiago de Chile. Learning and test data were collected during summer and springtime periods of 1990, 1992 and 1993. A neural ...
Learning the prediction error for improving an analytical-based prediction (object-model) system for manipulation tasks
(2018)
One of the main tasks in robotics today, is to
bring robots closer to humans in everyday situations. This
requires the robot to understand how its environment (objects,
people, conditions) behaves. One method that tries ...
Hybrid modeling and predictive control for hydrometallurgical processes
(IEEE, 2014)
Model-based control strategies rely heavily on precise models to make accurate predictions. In mineral processing, particularly, due to complexities such as strong nonlinearities, variable coupling, time varying parameters, ...
A comparison of modeling techniques to predict hydrological indices in ungauged rivers
(Asociación Ibérica de Limnología (AIL), 2020)