This paper deals with both introducing novel technique of calculating population diversity and analyzing the existing ones. This motivation to investigate new methods of determining population diversity lies in significant disadvantages of commonly used techniques, particularly the ones that operate in a parameter space. The problem with these methods is that they can produce inexact information about population state, e.g. indicate high diversity when it is far from being high. For the purpose of eliminating these problems, new diversity mechanisms are investigated. The main idea was to use the information that is contained in the matrix with all mutual distances between individuals. New mechanism can be employed within a standard parallel search algorithms (whether as analyzing or guiding mechanism), or in general, as a mechanism for determining how well does the finite set of points sample a compact region of space.

This paper examines capabilities of Artificial Neural Network (ANN) regarding control of a heavy vehicle seat with semi-active damper. Matlab and its sub-application Simulink are used as a tool for developing simulation model of the driver seat in the heavy vehicles. The seat model with semiactive damper is built modularly by forming each of its components separately. Designed control model was tested in Matlab/Simulink, and then was verified on experimental setup, installed on the Department for Automatic Control of the Friedrich Alexander University in Erlangen Nuirnberg. After introductory remarks, this work considers description of the seat with semi active damper including mechanical characteristics and mathematical description of major components, theoretical remark about ANNs, control system description and implementation on experimental setup, using dSPACE module.

This paper presents capabilities of fuzzy logic in longitudinal vehicle guidance. Two aspects in automated driving are presented. The first is trajectory generation for longitudinal vehicle guidance, where the real driver is replaced by fuzzy inference system. The second aspect is design of fuzzy controller which can be implement for leading ideal trajectory in longitudinal direction. Design of fuzzy system is realized in MATLAB environment where the vehicle dynamic is known. This dynamic is result of identification methods realized on the Institute of Automatic Control at the University of Erlangen-Nurnberg. Experimental results for the longitudinal vehicle guidance have been obtained by use of the Audi test vehicle equipped with sensors and control devices.

This paper describes a new algorithm for elimination of DC component in the current which appears during the fault condition in power system. The algorithm is very simple and convenient for implementation in numerical protection systems without rigid requirements on the speed of operation (medium voltage level feeder protections). This algorithm is described, the area of its possible application is emphasized, and the results of simulation conducted in MATLAB are given

In this paper, capabilities of a feed-forward neural network regarding control of the complex object are investigated. Neural controllers have been trained by a genetic algorithm with adaptive mutation and crossover probabilities. A specific model of aggressive selection operator is proposed along with one way of co-evolution of the crossover and mutation rates. Also, different mechanisms of operator adaptation were compared in sense of resulting controller performance. Finally, the measurement results, taken from the object (hydraulically driven two-joint robot arm) are presented.

The purpose of this paper is to show a simple ability of using neural networks in longitudinal vehicle guidance. The main motivation is an opportunity of neural networks to learn from acquired real driver data, as well as to reproduce many driver behaviour styles raging from extremely comfort to extremely sportive ones. This possibility is shown with a simulated model based longitudinal trajectory generation. This model has used an adjustable comfort parameter for different sorts of driver behaviour. Experiment results, obtained with Audi test vehicle, are also presented.

In terms of reducing efforts of an animator in creating facial animation keyframes we developed a system for automatic keyframe generation using MaxScript control script. Input parameter for the script is a parameter file containing phonemes of the prerecorded soundtrack and their durations. Recognition of phonemes is done by an LVQ neural network. After keyframes are created by the script, the animator is able to perform fine tuning and adding facial expressions of the emotions.

The purpose of this paper is to show a simple ability of a neural network usage in longitudinal vehicle guidance for the comfort adjustment. It gives a short overview of a trajectory generation algorithm as well as comfort adjustment for longitudinal movement using neural networks. The algorithm for longitudinal trajectory generation was implemented in AUDI test vehicle and the results have been shown. Also, two concepts of comfort adjustment using neural networks were also presented. The comfort adjustment was associated with the certain driver tracking style ranging from extremely comfort to extremely sportive ones

This paper presents the open hierarchical architecture of mobile robot realized at the Faculty of Electrical Engineering, University of Sarajevo. The basic idea during development was to enable simple implementation of algorithms for control of mobile robot, without large interventions on hardware, and to avoid complex software implementation of algorithms. MATLAB was used as basic development tool at the highest hierarhical level, considering its flexibility, as well as numerous high-level functions offered by MATLAB. As an illustration, the results achieved in development of fuzzy algorithm for navigation of mobile robot in unknown environment with obstacle avoidance, and the simplicity of its interactive modification will be demonstrated.

Thepurpose ofthis paperistoshowasimple ability ofa neuralnetworkusageinlongitudinal vehicle guidance forthecomfortadjustment. Itgivesa short overview ofa trajectory generation algorithm aswellas comfort adjustment forlongitudinal movementusing neural networks.The algorithm for longitudinal trajectory generation wasimplemented inAUDItestvehicle andthe results havebeen shown.Also,twoconcepts ofcomfort adjustment using neural networks werealsopresented. The comfort adjustment wasassociated withthecertain driver tracking style ranging fromextremely comfort toextremely sportive ones.

In this paper, a procedure of building the mobile robot platform is described. The main objective was to develop a system suitable for testing various velocity/position control and/or navigation algorithms without any major interventions on hardware or software structure. In order to achieve that goal, a modular hierarchical structure was developed. This type of structure has all the advantages of modular hardware and software architectures and is open for further upgrades. Another goal was to shorten the time between the idea generation and the implementation of the control algorithm itself. This was accomplished by making possible the generation and implementation of the algorithm in MATLAB environment. In this way, the system becomes more suitable for educational purposes.

This paper presents one method for measurement of phase shift between signals in electric power systems (EPS), such as voltages or currents. The presented algorithm is very simple and efficient, and it can be used for purposes of protection, control and measurement in EPS, as well. The algorithm is based on mathematically simple expressions, which do not require high processing power, so it is convenient for single chip applications. This algorithm is considered with high and low sampling rate, and proper pre-processing of signal in integrated data acquisition and control systems in EPS is proposed. It is shown that the achieved accuracy can satisfy requests of the intended application.