Authors: None

Abstract:

Keywords:

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.90001

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: ---

Authors: None

Abstract:

Keywords:

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.90002

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: ---

Authors: Pizzileo, B.; Li, K.; Irwin, G. W.

Abstract: Reduced complexity in a fuzzy neural network eases the computational burden of construction and training from data, while enhancing the interpretability of the final model. Such structure optimisation can be done either by adjusting the number of inputs and the size of the rule set. In the literature these have generally been addressed independently (Sugeno and Yasukawa [1993], Hong and Harris [2003]). This paper presents a new algorithm where both structural parameters for a fuzzy neural network model are optimized together. Results from simulation examples are given to illustrate the new approach and confirm its advantage over existing methods.

Keywords:

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00003

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 1-6

Authors: Christodoulou, M. A.; Evaggelos, P.; Stavros, S.

Abstract: the regulation of enzyme activity is crucial to the regulation of protein interactions within signal transduction pathways. The aim of this project is the implementation of a Direct Adaptive method for regulating enzyme kinetic reactions. For this purpose a Direct Adaptive Control method using RHONNs for affine in the control non-linear dynamical systems is implemented.

Keywords: protein kinase C pathway,regulation of enzyme,direct adaptive control,RHONNs

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00004

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 7-12

Authors: Jiménez, Agustín; Al Hadithi, Basil M.; Matía, Fernando

Abstract: A new, simple and less computational approach is presented to improve the local and global modeling capability of Takagi-Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main drawback of T-S identification method is that it can not be applied when the membership functions are overlapped by pairs. This restricts the application of the T-S model because this type of membership function has been widely used during the last two decades in the stability, controller design of fuzzy systems and is popular in industrial control applications. The method developed here can be considered as a generalized version of T-S fuzzy identification method with optimized performance in approximating nonlinear functions. Various examples are chosen to examine the remarkable performance of the proposed method and the high accuracy obtained in approximating nonlinear systems locally and globally in comparison with the original T-S model.

Keywords: nonlinear systems,fuzzy systems,Takagi-Sugeno fuzzy model,universal approximators,optimization

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00005

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 13-19

Authors: Kase, Wataru; Mutoh, Yasuhiko

Abstract: In this paper, it will be clear the structure of the Iterative Learning Control (ILC) based on the inverse system. Moore-Penrose pseudo-inverse of a Toeplitz matrix will be investigated to analyze the learning gain matrix and will be derived the cascade controller transfer function matrix. From these investigations, the critical points of ILC based on the gradient will be issued.

Keywords: iterative learning control,discrete-time systems,gradient method,Toeplitz matrix,interactor

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00006

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 20-24

Authors: Taleb, Rachid; Meroufel, Abdelkader; Wira, Patrice

Abstract: A neural implementation of a harmonic elimination strategy for the control a uniform step asymmetrical 11-level inverter is proposed and described in this paper. A Multi-Layer Perceptrons (MLP) neural network is used to approximate the mapping between the modulation rate and the required switching angles. After learning, the neural network generates the appropriate switching angles for the inverter. This leads to a low-computational-cost neural controller which is therefore well suited for real-time applications. This neural approach is compared to the well-known sinusoidal Pulse-Width Modulation (PWM). Simulation results demonstrate the technical advantages of the neural implementation of the harmonic elimination strategy over the conventional method for the control of an uniform step asymmetrical 11-level inverter. The approach is used to supply an asynchronous machine and results show that the neural method ensures a highest quality torque by efficiently canceling the harmonics generated by the inverter.

Keywords: uniform step asymmetrical multilevel inverter,harmonics elimination strategy,artificial neural networks,multi-layer perceptron,sinusoidal pulse-width modulation

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00007

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 25-30

Authors: Halbwachs, Damien; Wira, Patrice; Mercklé, Jean

Abstract: Two new neural approaches for on-line frequency estimation of a sinusoidal signal perturbed by harmonic distortions and random noise are presented in this paper. These approaches are based on an iterative formulation of the signal which is learned by Adaline neural networks. Adalines are very simple and efficient artificial neural networks, they can be easily implemented on a digital signal processor. The proposed approaches are therefore suitable for real-time implementations and their performance and robustness are evaluated by numerical simulations and experimentally under different severe operating conditions. The proposed neural estimators are favorably compared to the classical zero-crossing method, to an active notch filter method, and to a previous Adaline based-method. Furthermore, all these methods are also evaluated in terms of computational costs.

Keywords: frequency estimation,frequency tracking,Adaline,artificial neural networks,power distribution network

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00008

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 31-36

Authors: Köroglu, Muhammed T.; Önkol, Mert; Efe, Mehmet Önder

Abstract: This paper presents an experimental framework to describe the dynamic behavior of brushless direct current (BLDC) motors, which are frequently used in unmanned aerial vehicle (UAV) applications. Typically these applications require varying the angular speeds of motors which have to be precise parts of the dynamic model. The experimental setup is a motor/propeller pair equipped with an electronic speed controller. The substantial contribution of the paper is to incorporate the voltage drop caused by the consumed power and the alleviation of the modulation effect on the measured battery voltage. The consequence of the voltage drop is to obtain different angular speeds under same excitation inputs. A Neural Network (NN) based approach is chosen to handle this modeling issue. Levenberg-Marquardt algorithm is used to tune the adjustable parameters of NN, which is trained offline using the data observed through a set of experiments. Some experimental validation results are presented to justify the model.

Keywords:

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00009

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 37-42

Authors: Eresen, Aydín; Imamoglu, Nevrez; Efe, Mehmet Önder

Abstract: In this paper, detecting and tracking of a car is aimed using a stationary camera system. Background subtraction is used to detect motion and Kalman filter is used for tracking of a moving car. Classification of the car is accomplished utilizing Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs). In using SVMs and ANNs, some features should be extracted from Region of Interest (RoI). Before the extraction, image enhancement methods are used and then by using Discrete Wavelet Transform (DWT), the features are represented in different frequency scales. The current work compares the performances of ANNs trained via Levenberg-Marquardt optimization technique, Least Squares Support Vector Classification (LS-SVC) and ε Support Vector Classification (ε-SVC).

Keywords: neural networks,support vector machines,image segmentation,image recognition

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00010

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 43-48

Authors: Azar, F. Esmaeilzadeh; Perrier, M.; Srinivasan, B.

Abstract: Extremum-seeking schemes are real-time optimization methods that control the gradient to zero. Most of these methods can converge only to the closest local optimum, though recently, some schemes have been proposed for global optimization of a restrictive class of nonlinear maps. In this paper, the multi-unit optimization framework is used, where an offset is introduced between the inputs of two identical units and the gradient is estimated by finite difference. It is shown that if the offset is reduced to zero, the system can be made to converge to the global optimum for all nonlinear continuous static, scalar maps. Several illustrative examples are presented to show the capability of this methodology.

Keywords:

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00011

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 49-54

Authors: Khaldi, Mohamad R.; El Abiad, Hassan H.

Abstract: Scaled-model helicopters are highly nonlinear, coupled, and unstable machines. They have fast response and controlling them is very complicated and need high degree of precision. In this paper, a detailed nonlinear model is derived. An optimal controller that is based upon state estimation is designed and implemented for each of the control inputs using a linearized model around an unaccelerated hovering motion. The optimal linear controller was then applied to the nonlinear model. In addition, input/output measurements of the nonlinear model were used to train the Multi-Layer Neural Networks (MLNNs) of the Nonlinear AutoRegressive with Moving Average (NARMA-L2) controller. Then, NARMA-L2 was applied to the nonlinear model and the results were compared with both the classical, namely PI-D, and the optimal control.

Keywords:

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00012

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 55-60

Authors: Królikowski, Andrzej; Horla, Dariusz

Abstract: In this paper, a suboptimal solution to the dual control problem for discrete-time stochastic systems under the amplitude-constrained control is considered. The objective of the control is to minimize the two-step quadratic cost function for the problem of tracking the given reference sequence. The presented approach is based on the MIDC (Modified Innovation Dual Controller) derived from an IDC (Innovation Dual Controller) and the TSDSC (Two-stage Dual Suboptimal Control. As a result, a new algorithm, i.e. the two-stage innovation dual control (TSIDC) algorithm is proposed. The standard Kalman filter equations are applied for estimation of the unknown system parameters. Example of second order system is simulated in order to compare the performance of proposed control algorithms. Conclusions yielded from simulation study are given.

Keywords: input constraint,suboptimal dual control

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00013

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 61-66

Authors: Gessing, Ryszard S.

Abstract: It is shown how to create the continuous system equivalent to the system with sliding mode control. In the case of minimum phase plants, the system arises from the replacement of the relay by some appropriate saturation-type nonlinearity. The latter may be implemented using the amplifier with high gain and saturation with constraints of the control determined by the switched magnitudes of the relay. In the case of nonminimum phase plants it is noted that similar equivalence exists for the continuous and relay system with parallel compensator. The latter system may be treated as the system with modified sliding mode control. In the equivalent continuous system the chattering effect, related with sliding mode control doesn't exist.

Keywords: sliding mode control,continuous control,constrained control,parallel compensator,nonminimum phase plants

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00014

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 67-72

Authors: Baykara, Mehmet; Öznergiz, Ertan; Özsoy, Can; Demir, Ali; Gülsen, Salih

Abstract: This paper presents the modeling and model predictive control based on state-space model of the air jet texturing and twisting machine. The system model shows the tension change in the twisting process. In designing of the Model Predictive Controller, two major objectives are considered. The first one is that the yarn tension in twisting process tracks a given reference tension; the second one is that the yarn tension with texturing process which is assumed as a step disturbance has to track the same ideal tension value. To verify the control algorithm performance, the proposed algorithm is compared with a PID controller designed with Ziegler-Nichols method. All computer simulations were completed in MIDSYS toolbox and MATLAB Simulink. The simulation study shows that the proposed model predictive control is an improvement over the PID controller for any control inputs.

Keywords: air-jet texturing and twisting,tension control,system identification,ARX,state-space model predictive control,PID controller

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00015

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 73-78

Authors: Christodoulou, Manolis; Boutalis, Yiannis; Theodoridis, Dimitrios

Abstract: The indirect adaptive regulation of unknown nonlinear dynamical systems under the presence of dynamic and parameter uncertainties, is considered in this paper. The method is based on a new Neuro-Fuzzy Dynamical Systems definition named Fuzzy-Recurrent High Order Neural Network (F-RHONN), which however takes into account the fuzzy output partitions of the initial fuzzy dynamical system (FDS) operating in conjunction with appropriate HONNFs, that approximates the fuzzy rules. The proposed scheme does not require a-priori experts' information on the number and type of input variable membership functions making it less vulnerable to initial design assumptions. Once the system is identified around an operation point, it is regulated to zero adaptively. Weight updating laws for the involved HONNFs are provided, which guarantee that under the presence of 'small' dynamic uncertainties both the identification error and the system states reach zero exponentially fast, while keeping all signals in the closed loop bounded. The existence of the control signal is always assured by introducing a method of parameter hopping, which is incorporated in the weight updating law. The applicability is tested on the Lorenz model, where it is shown that by following the proposed procedure one can obtain asymptotic regulation quite well in the presence of unmodeled dynamics.

Keywords: neuro-fuzzy systems,indirect adaptive control,parameter hopping

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00016

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 79-85

Authors: Francken, Julien; Maquin, Didier; Ragot, José; Bèle, Bertrand

Abstract: In the steel industry, the determination of the control system set-points of batch processes is a common problem. It consists in adjusting the set-points in order to reach the given product specifications thanks to a process model. Small changes in operating conditions may impact final product quality. This is particularly true for the Basic Oxygen Furnace (BOF) where the information collected during a specific batch serves to adjust the set-points of the next batch. For being able to control that type of process, measurements must be made coherent and it may be convenient to use data reconciliation procedure. The proposed paper describes a method allowing simultaneous data reconciliation and model parameter estimation. Parameter estimation results can either be used to update the process model or to detect abnormal parameter variations due, e.g. to fouling, corrosion, degradation of parts of the process.

Keywords: data reconciliation,parameter estimation,set-point control,batch process,estimation techniques

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00017

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 86-91

Authors: Kocijan, Juš; Azman, Kristjan

Abstract: This paper describes an application of the method for modelling nonlinear dynamic systems from measurement data. The method merges the linear local model blending approach in the velocity-based linearisation form with Bayesian Gaussian process modelling. The new Fixed-Structure Gaussian Process model has a predetermined linear model structure with varying and probabilistic parameters represented by Gaussian process models. These models have several advantages for the modelling of local model parameters as they give us adequate results, even with small data sets. Furthermore, they provide a measure of confidence in the prediction of the varying parameters and information about the dependence of the parameters on individual inputs. The Fixed-Structure Gaussian Process model can be used for the extended local linear equivalence class of nonlinear systems. The modelling method is applied to modelling of a semi-industrial gas-liquid plant that exhibits variable dynamics depending on its operating region.

Keywords: nonlinear models,identification,Gaussian processes,linear parameter varying model

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00018

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 92-97

Authors: Katic, Duško M.; Rodic, Aleksandar D.

Abstract: This paper presents a novel dynamic control approach to acquire biped walking of humanoid robots focussed on policy gradient reinforcement learning with fuzzy evaluative feedback. The proposed structure of controller involves two feedback loops: conventional computed torque controller including impact-force controller and reinforcement learning computed torque controller. Reinforcement learning part includes fuzzy information about Zero-Moment Point errors. To demonstrate the effectiveness of our method, we apply it in simulation to the learning of a biped walking.

Keywords:

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00019

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 98-103

Authors: Matsuda, Nobuo; Tokutaka, Heizo; Oyabu, Matashige

Abstract: In this paper, we propose two methods for determining class borders. One approximates the borders on a SOM from the nearest neighbor datasets of different classes. The other especially approximates the borders on a spherical SOM using the coordinate system of a polygon surface. Both methods decide the border on the SOM using the characteristics of the SOM which can map a high dimensional dataset onto a low dimensional map which is usually 2 or 3 dimensional. Using the iris dataset of Fisher and the wine dataset, it is shown that the proposed methods allow the class borders to be successfully visualized, and in a comprehensible manner, and that the methods can improve the accuracy of a cluster analysis. The verification of the decision border, computed with one of the proposed methods, was performed with the spherical SOM and the dendrogram. The advantages of visualization were successfully demonstrated using two benchmark databases.

Keywords: decision border,spherical SOM,cluster analysis,visualization

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00020

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 104-108

Authors: Cheng, Chi-Bin

Abstract: This study proposes a mixed-integer programming with fuzzy constraints for solving the bidding problem in a reverse auction environment. Suppliers' optimum bid price is determined through the compromise between profitability of the bid and possibility to win the contract. The proposed model embeds the advanced available-to-promise (AATP) concept in order to support accurate computation of profit and customer order promising. Moreover, the feasible bid price is constrained by a fuzzy upper bound to model the decision-maker's subjective judgment. A genetic algorithm is formulated to solve the problem. Performance of the proposed approach is evaluated through computer simulated experiments.

Keywords: reverse auction,bidding,advanced available-to-promise,fuzzy mathematical programming,genetic algorithm

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00021

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 109-114

Authors: Orlowski, Przemysław

Abstract: Classical linear finite impulse response filters (FIR) with constant coefficients have solid and comprehensive theoretical foundations and design methods. The main advantage of using FIR filters is good linearity of phase diagram. Although filters with constant coefficients guarantee particular properties in frequency domain, i.e. noise damping, they also increase rise time for rapid signal changes. In order to avoid such blurring effects a low-pass parameter varying FIR filter is proposed. To synthesize the filter two cut-off frequencies are needed accompanied with given filter order, shape tuning function and threshold detection condition for sequential operation. Properties of the filter with time-varying coefficients are analyzed using proposed previously by the author simplified frequency approach for time-varying systems. The frequency approach for filter analysis takes advantage of SVD-DFT transformation of linear time-varying discrete-time system, employing singular value decomposition, discrete Fourier transformation and power spectral density properties. Considerations are illustrated by numerical example.

Keywords: digital filters,finite impulse response filters,linear parameter varying systems,discrete-time systems,time-varying systems,non-stationary systems

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00022

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 115-119

Authors: Önel, Izzet Y.; Caglar, Engin; Duyar, Ahmet

Abstract: This paper deals with predictive maintenance and its importance on industrial applications. After introduction, brief information is given about causes of electrical motor failures and then, predictive maintenance concept is introduced. Next, most popular techniques are told briefly. Model based fault detection technique which is utilized by Artesis MCM (Motor Condition Monitor) unit is mentioned. A case study is given at the end of the paper.

Keywords: predictive maintenance,condition monitoring systems,model based automatic fault diagnosis,artesis MCM

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00023

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 120-125

Authors: Alonso, L.; Oria, J. P.; Fernández, M.; Rodríguez, C.

Abstract: The system presented is an expert system capable of taking decisions to avoid collisions in urban traffic or to minimize the damages, due to a lack of attention or some other unexpected situation. It is based on the use of simple and inexpensive ultrasonic transducers as sensing elements for the driver support. The rule-based expert system is able to detect a potentially dangerous situation and act accordingly on the brake. Simulations demonstrates the validity of the system to improve the active safety of vehicles.

Keywords: expert system,car dynamics,ultrasound,safety distance,driving-aid systems,artificial intelligence

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00024

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 126-130

Authors: Torigoe, S.; Igarashi, R.; Komatsu, T.; Takeno, J.

Abstract: We have developed a robot that is capable of consciousness and emotions similar to humans. We represented consciousness in this robot, added emotions to assist in the evolution of the conscious system of the robot, and successfully performed mirror image cognition tests with the robot. Emotion is a basic function for the robot to enable it to avoid life-threatening situations. We now wish the robot to evolve and develop by itself. Humans continue to develop themselves by accumulating experiences. We believe that robots of the future should also be able to evolve and develop by themselves by repeating learning or accumulating experiences. This paper reports on a robot that has functions similar to the consciousness and emotions of humans and is capable of avoiding physical danger to itself by remembering its past experiences.

Keywords: neural networks,recognition,robotics,consciousness,emotion,feelings,experiences

Digital Object Identifier (DOI): 10.3182/20090921-3-TR-3005.00025

Conference: 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)

Location: , Turkey

Start Date: Mon Sep 21 2009 - End Date: Wed Sep 23 2009

Page Numbers: 131-136