In this paper, with a new look at emotional controller and modifying its structure; a novel approach to hierarchical control of large-scale systems is introduced. Design of controller is founded on emotional learning and the control system consists of neuro-fuzzy controller, whose weights are updated according to emotional signals. This signal is produced in a block called critic, whose job is ...

In this paper, an antilock–antiskid braking system controller, which has been designed for stability enhancement of vehicles during braking and turning, is presented. Using available signals, a novel structure is proposed for vehicle stability improvement for critical driving conditions such as braking on slippery or μ-split road surfaces. In conventional vehicles, undesired lane changes may oc...

The goal of this work is to propose a learning procedure for fuzzy systems. Fuzzy systems are able to treat uncertain and imprecise informations. They have a capability to express knowledge in the form of linguistic rules. Their drawbacks are caused mainly by the diiculty of deening accurate membership functions and lack of a systematic procedure for the transformation of the expert knowledge i...

Abstract In order to actively control combustion reaction, this study proposes an adaptive neuro-fuzzy (ANFIS) scheme of interaction between premixed reaction and acoustic flame perturbation where the pressure movement will be considered as model perturbation. Using Cantera database, it is possible investigate mechanisms by which process interacts with acoustic, vorticity, entropy waves. A well...