3 research outputs found
Recursive neuro fuzzy techniques for online identification and control
Dissertação para obtenção do Grau de Mestre em
Engenharia Electrotécnica e de ComputadoresThe main goal of this thesis will be focused on developing an adaptative closed loop
control solution, using fuzzy methodologies. A positive theoretical and experimental
contribution, regarding modelling and control of fuzzy and neuro fuzzy systems, is expected
to be achieved.
Proposed non-linear identification solution will use for modelling and control, a recurrent
neuro fuzzy architecture. Regarding model solution, a state space approach will be
considered during fuzzy consequent local models design. Developed controller will be
based on model parameters, being expected not only a stable closed loop solution, but
also a static error with convergence towards zero. Model and controller fuzzy subspaces,
will be partitioned throughout process dynamical universe, allowing fuzzy local models
and controllers commutation and aggregation.
With the aim of capturing process under control dynamics using a real time approach,
the use of recursive optimization techniques are to be adopted. Such methods will be
applied during parameter and state estimation, using a dual decoupled Kalman filter extended
with unscented transformation.
Two distinct processes one single-input (SISO) other multi-input (MIMO), will be used
during experimentation. It is expected from experiments, a practical validation of proposed
solution capabilities for control and identification. Presented work will not be
completed, without first presenting a global analysis of adopted concepts and methods,
describing new perspectives for future investigations
Intento flexiexistencialista
Intento / coordenação [de] Mário João Alves Chaves. - Lisboa : Universidade Lusíada, 2022. - ISBN 978-989-640-253-2. - P. 1-184