Sharif Digital Repository

For the first time in this paper, Brain Emotional Learning Based Intelligent Controller (BELBIC) is applied to attitude control of a Quadrotor. BELBIC controller is designed based on the computational model of emotional learning process in mammalian brain limbic system. Proposed control algorithm is employed because of the learning ability and independency to system model and also satisfactory performances dealing with disturbances and changing in system parameters. Quadrotor is an Unmanned Aerial Vehicle (UAV) which has the capability of Vertical Take-Off and Landing (VTOL). Simulation results of controlling Quadrotor with BELBIC are addressed. Also pitch angle disturbance is applied due to... 

In this paper, a biologically motivated controller based on a mammalian limbic system called Brain Emotional Learning Based Intelligent Controller (BELBIC) is used for speed control of a Digital Servo System. The proposed controller is applied experimentally to a laboratory Digital Servo System 1 via MATLAB external mode. Comparing results of the proposed controller with conventional PID controller shows satisfactory performance including faster response and lower overshoot  

During the milling process, one of the most important factors in reducing tool life expectancy and quality of workpiece is the chattering phenomenon due to self-excitation. The milling process is considered as a MIMO strongly coupled nonlinear plant with time delay terms in cutting forces. We stabilize the plant using two independent Emotional Learning-based Intelligent Controller (ELIC) in parallel. Control inputs are considered as forces Ux and Uy in two directions x and y, which are applied by the piezoelectrics. The ELIC consists of three elements; Critic, TSK controller and the learning element. The results of the ELIC have been compared with a Sliding Mode Controller (SMC). The... 

Efforts have been targeted at providing a comprehensive simulation of a centrifugal compressor undergoing surge. In the simulation process, an artificial neural network was utilized to produce an all-inclusive performance map encompassing those speeds not available in the provided curves. Two positive scenarios for the shaft speed, constant, and variable, were undertaken, and effects of load line on the dynamic response of the compressor have been studied. In order to achieve high-fidelity simulation in the variable speed case, an artificial neural network was utilized to produce an all-inclusive performance map encompassing those speeds not available in the provided curves. Moreover,... 

In this research an intelligent emotional learning controller, Takagi- Sugeno- Kang (TSK) is applied to govern the dynamics of a novel Ionic-Polymer Metal Composite (IPMC) actuated manipulator. Ionic-Polymer Metal Composites are active actuators that show very large deformation in existence of low applied voltage. In this research, a new IPMC actuator is considered and applied to a 2-dof miniature manipulator. This manipulator is designed for miniature tasks. The control system consists of a set of neurofuzzy controller whose parameters are adapted according to the emotional learning rules, and a critic with task to assess the present situation resulted from the applied control action in... 

The model of emotional masks is a newly developed AI paradigm based on Minsky's model of emotional mind in his recent book "The emotion machine". The model takes a resource management approach toward modeling the mind and views different processes of mind as resources that need to be managed. In the present work an intelligent controller (SCELIC) is developed based on the model of emotional masks. SCELIC is a model free controller which advantages from several learning tasks. Multiple learnings and adaptive structure make it a powerful adaptive and self-learning tool that performs the tasks of system identification and control in parallel. Although the test-bed considered here is a nonlinear... 

The aim of this article is design, fabricate, and control a conceptual prototype of a flexible wearable robot to increase fingers’ force using a novel cable mechanism. In this robot, force and position are controlled in separate phases by a fuzzy system equipped with emotional learning. A Flexible structure has been chosen for this robot, because flexible gloves are lighter and much more suitable for use in daily tasks compared to rigid structures. Since this system is supposed to be substituted for weak or damaged limb, it should have a behavior similar to the body organs as much as possible. Therefore, a novel mechanism, inspired by the natural movement mechanism of the human hand, has... 

The design and evaluation of a novel approach to reactor core power control based on emotional learning is described. The controller includes a neuro-fuzzy system with power error and its derivative as inputs. A fuzzy critic evaluates the present situation, and provides the emotional signal (stress). The controller modifies its characteristics so that the critic's stress is reduced. Simulation results show that the controller has good convergence and performance robustness characteristics over a wide range of operational parameters. © 2008 Elsevier Ltd. All rights reserved  

The aim of this article is design, fabricate, and control a conceptual prototype of a flexible wearable robot to increase fingers’ force using a novel cable mechanism. In this robot, force and position are controlled in separate phases by a fuzzy system equipped with emotional learning. A Flexible structure has been chosen for this robot, because flexible gloves are lighter and much more suitable for use in daily tasks compared to rigid structures. Since this system is supposed to be substituted for weak or damaged limb, it should have a behavior similar to the body organs as much as possible. Therefore, a novel mechanism, inspired by the natural movement mechanism of the human hand, has... 

The aim of this article is design, fabricate, and control a conceptual prototype of a flexible wearable robot to increase fingers’ force using a novel cable mechanism. In this robot, force and position are controlled in separate phases by a fuzzy system equipped with emotional learning. A Flexible structure has been chosen for this robot, because flexible gloves are lighter and much more suitable for use in daily tasks compared to rigid structures. Since this system is supposed to be substituted for weak or damaged limb, it should have a behavior similar to the body organs as much as possible. Therefore, a novel mechanism, inspired by the natural movement mechanism of the human hand, has... 

In this paper, we consider a control strategy of multi-robot systems, or simply, swarms, based on emotional control technique. First, we briefly discuss a "kinematic" swarm model in n-dimensional space introduced in an earlier paper. In that model, motion of every swarm member is governed by predefined inter-individual interactions. Limitations of every member's field of view are also considered in that model. After that, we consider a general model for vehicle dynamics of each swarm member, and use emotional control theory to force their motion to obey the dynamics of the kinematic model. Based on the kinematic model, stability (cohesion) analysis is performed and coordination controller.is... 

In this paper a novel approach based on the emotional learning is proposed for improving the load-frequency control (LFC) system of a two-area interconnected power system with the consideration of generation rate constraint (GRC). The controller includes a neuro-fuzzy system with power error and its derivative as inputs. A fuzzy critic evaluates the present situation, and provides the emotional signal (stress). The controller modifies its characteristics so that the critic's stress is reduced. The convergence and performance of the proposed controller, both in presence and absence of GRC, are compared with those of proportional integral (PI), fuzzy logic (FL), and hybrid neuro-fuzzy (HNF)... 

Fault detection has always an important role in maintaining the system stability and assuring satisfactory and safe operation. In this paper a method based on system identification is used for fault detection on a nuclear reactor. The combination of Extended Kalman Filter and recursive Least Square are used to identify the system parameters. Another goal of this paper is design of a fault tolerant control system for a nuclear reactor during power change operation. The proposed controller is an adaptive neuro-fuzzy controller based on emotional learning. Performance of the controller in term of transient response and robustness against failure is very good and outstanding  

In this paper, we consider a control strategy of multi-robot systems, or simply, swarms, based on emotional control technique. First, we briefly discuss a "kinematic" swarm model in n-dimensional space introduced in an earlier paper. In that model, motion of every swarm member is governed by predefined inter-individual interactions. Limitations of every member's field of view are also considered in that model. After that, we consider a general model for vehicle dynamics of each swarm member, and use emotional control theory to force their motion to obey the dynamics of the kinematic model. Based on the kinematic model, stability (cohesion) analysis is performed and coordination controller is...