FPGA-implementation of PID-controller by differential evolution optimization

We will describe an FPGA implementation of PID-controller that uses differential evolution to optimize the coefficients of the PID controller, which has been implemented in VHDL. The original differential evolution algorithm was improved by ranking based mutation operation and self-adaptation of mutation and crossover parameters. Ranking-based mutation operation improves the quality of solution, convergence rate and success of optimization. Due to the self adaptive control parameters, the user does not have to estimate the mutation and crossover rates. Optimization have been performed by calculating for each generation fitness value by means of trial parameters. The final optimal parameters are selected based on the minimum fitness.fi=vertaisarvioitu|en=peerReviewed

Fast fixed-point bicubic interpolation algorithm on FPGA

We propose a fast fixed-point algorithm for bicubic interpolation on FPGA. Bicubic interpolation algorithms on FPGA are mainly used in image processing systems and based on floating-point calculation. In these systems, calculations are synchronized with the frame rate and reduction of computation time is achieved designing a particular hardware architecture. Our system is intended to work with images or other similar applications like industrial control systems. The fast and energy efficient calculation is achieved using a fixed-point implementation. We obtained a maximum frequency of 27.26 MHz, a relative quantization error of 0.36% with the fractional number of bits being 7, logic utilization of 8%, and about 30% of energy saving in comparison with a C-program on the embedded HPS for the popular Matlab test function Peaks(25,25) data on SoCkit development kit (Terasic), chip: Cyclone V, 5CSXFC6D6F31C8. The experiments confirm the feasibility of the proposed method.fi=vertaisarvioitu|en=peerReviewed

A Review of Indocyanine Green Fluorescent Imaging in Surgery

The purpose of this paper is to give an overview of the recent surgical intraoperational applications of indocyanine green fluorescence imaging methods, the basics of the technology, and instrumentation used. Well over 200 papers describing this technique in clinical setting are reviewed. In addition to the surgical applications, other recent medical applications of ICG are briefly examined

FPGA–implementation of PID-controller by differential evolution optimization

We will describe an FPGA implementation of PID-controller that uses differential evolution to optimize the coefficients of the PID controller, which has been implemented in VHDL. The original differential evolution algorithm was improved by ranking based mutation operation and self-adaptation of mutation and crossover parameters. Ranking-based mutation operation improves the quality of solution, convergence rate and success of optimization. Due to the self-adaptive control parameters, the user does not have to estimate the mutation and crossover rates. Optimization have been performed by calculating for each generation fitness value by means of trial parameters. The final optimal parameters are selected based on the minimum fitness

Genetic Algorithm Based Software Testing

In this work we are studying possibilities to test software using genetic algorithm search. The idea is to produce test cases in order to find problematic situations like processing time extremes. The proposed test method comes under the heading of automated dynamic stress testing. Keywords: genetic algorithms, software engineering, dynamic stress testing 1 Introduction Real-time software is increasingly applied to products in which failure may have severe consequences, thus the requirements for correctness and reliability are getting higher, too. In very reliable sequential programs, the rate of errors should be less than 10 errors/1000 lines of code, to avoid functional failure. Achieving this level is very labourious, because the amount of program testing work grows exponentially with code size. Testing software manually is slow, expensive and demands inventiveness. Automated testing can reduce both the time and costs needed for performing tests. Exhaustive test data generation is..

GA in program testing

. In this work were are studying the possibilities to test real time programs by genetic algorithms. The idea is to produce test cases that try to find the problematic cases e.g. the maximum response times a pilot we have used a power distribution relay software. Keywords: software engineering, real time programming, program quality, software testing 17.1 Introduction Whether a real time program meet the given time response requirements can be seen as an optimization problem: try to find the cases, which maximize the response. After we have found the most difficult cases we can start to analyse them and we can then try to handle them in such a way that the worst case either meets the requirements or we must look for further measures. The optimization (maximization) is usually quite difficult and there is not much known algorithms to choose from to solve it. In this work we propose that generic algorithm could be used in this kind of optimization problems. When this abstract was writt..