This paper presents a novel Brain Emotional Learning Based Intelligent Controller (BELBIC) for controlling some of the parameters, such as speed, torque, quadrature and direct axis current and voltage of an Interior Permanent Magnet Synchronous Motor (IPMSM). PI controllers are widely used as speed controllers in industries. IPMSMs are characterized as complex, highly non-linear and time-varyin...

One of the most important phenomena of some systems is chaos which is caused by nonlinear dynamics. In this paper, the new 3 dimensional chaotic system is firstly investigated and then utilizing an intelligent controller which based on brain emotional learning (BELBIC), this new chaotic system is synchronized. The BELBIC consists of reward signal which accept positive values. Improper selection...

Wireless sensor networks (WSNs) are composed of small sensing and actuating devices that collaboratively monitor a phenomena, process and reason about sensor measurements, and provide adequate feedback or take actions. One of WSNs tasks is event detection, in which occurrence of events of interest is detected in situ whenever and wherever they occur. Some examples of these events include enviro...

Conventional control systems often suffer from the coexistence of nonlinearity and uncertainty. This paper proposes a novel brain emotional neural network to support addressing such challenges. The proposed integrates wavelet into conventional learning network. is further enhanced by introduction recurrent structure employ two networks as channels therefore combines advantages function, mechani...

In this paper, we describe a multi agent controller for meeting different criteria, based on emotional learning. Our proposed controller is motivated by the affective and emotional faculties in human begins, which constantly evaluate the current states with respect to the achievement of the desired goals. For meeting different criteria, the controller consists of several critic agents that each...

Purpose – Intelligent control for unidentified systems with unstable equilibriums is not always a proper control strategy, which results in inferior performance in many cases. Because of the existing trial and error manner of the procedure in former duration of learning, this exploration for finding the appropriate control signals can lead to instability. However, the recent proposed emotional ...

anti-lock braking system (abs) is a nonlinear and time varying system including uncertainty, so it cannot be controlled by classic methods. intelligent methods such as fuzzy controller are used in this area extensively; however traditional fuzzy controller using simple type-1 fuzzy sets may not be robust enough to overcome uncertainties. for this reason an interval type-2 fuzzy controller is de...

An artificial neural network can be used as an intelligent controller to control non-linear, dynamic system through learning. It can easily accommodate non-linearities and time dependencies. Most common multi-layer feed-forward neural networks have the drawbacks of large number of neurons and hidden layers required to deal with complex problems and require large training time. To overcome these...

In this paper, an intelligent method called BELBIC (Brain Emotional Learning Based Intelligent Controller) is used to control of Locally Linear Neuro-Fuzzy Model (LOLIMOT) of Washing Machine. The Locally Linear Neuro-Fuzzy Model of Washing Machine is obtained based on previously extracted data. One of the important issues in using BELBIC is its parameters setting. On the other hand, the control...

In this paper a new control strategy based on Brain Emotional Learning (BEL) model has been introduced. A modified BEL model has been proposed to increase the degree of freedom, controlling capability, reliability and robustness, which can be implemented in real engineering systems. The performance of the proposed BEL controller has been illustrated by applying it on different nonlinear uncerta...