Genetic algorithm as self-test path and circular self-test path design method

The paper presents the use of Genetic Algorithm to search for non-linear Autonomous Test Structures (ATS) in Built-In Testing approach. Such structures can include essentially STP and CSTP and their modifications. Non-linear structures are more difficult to analyze than the widely used structures such as independent Test Pattern Generator and the Test Response Compactor realized by Linear Feedback Shift Registers. To reduce time-consuming test simulation of sequential circuit, it was used an approach based on the stochastic model of pseudo-random testing. The use of stochastic model significantly affects the time effectiveness of the search for evolutionary autonomous structures. In test simulation procedure, the block of sequential circuit memory is not disconnected. This approach does not require a special selection of memory registers such as BILBOs. A series of studies to test circuits set ISCAS’89 are made. The results of the study are very promising

An agent-based evolutionary approach for manufacturing system layout design

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de ComputadoresIn this thesis it is presented an approach to the problem of layout design for a manufacturing system, which is an important part of its design stage, given that it has influence in the system efficiency and, therefore, in its output rate and fault handling capabilities. The presented approach is based on a Genetic Algorithm (GA) that, by using information provided by the the user through an ontology file, and by using algorithms from graph-theory, designs the layout of a manufacturing system. The instances of the ontology represent manufacturing resources and their characteristics that, when they are being used by the algorithm, are encoded in chromosomes and in their genes. The algorithm begins with a number of chromosomes with low fitness which, with the directed evolution provided by the algorithm, that is restricted by the control parameters that might be tunned by the user, improve with the passing of the new generations. It is considered that the fittest solution is the one that connects, in order, all the resources required by the manufacturing plan, described in the ontology, without the occurrence of overlaps when the layout is constructed. The configuration presented by the transport system that handles parts and materials, in the selected layout, is only dependent on the available resources and on the fitness function used by the GA, being that the last cannot be changed by the user. This approach differs from others by positioning simultaneously all the components of the manufacturing system and not only workstations or transport system. The solution is directed to evolvable assembly systems, purpose for which it was implemented inside an agent, so it can be integrated in a Multiagent System (MAS) to be used in the control of a manufacturing system with minimal changes. Keywords: layout design, manufacturing system, multiagent system, ontology, genetic algorithm

A survey on fractional order control techniques for unmanned aerial and ground vehicles

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade