Interactive learning support system for geometric road design

This work has as objective to develop an interactive ambient that uses a computer, conceived to aid the geometric project of wheelwork highways, considering that educational softwares in the teaching-learning atmosphere has been more and more frequent in all the levels of the education. This way, it was made a research, involving the concepts of the learning process, that is, the educational paradigms, ergonomics of man/machine interface and its pedagogic involvement. A target public, the course of Civil Engineering, was chosen with the purpose of elaborating the calculations involved in the geometric project of highways, and the coalition of those information converged for the interactive system elaboration, generating a rich source of knowledge. The focus of this work is centered in two properties: usability (with an ergonomic character) and learning (with a pedagogic character), facilitating the learning of the system, as well as the learning in the system. So a simulator was conceived to work in agreement with the instructional modules, indicating that there is integration of the approaches of larger conformity in usability and the learning approaches, which are defined to validate the pedagogic quality of the software. The process teaching-learning should prioritize the students' learning on the form of the teachers’ teaching, because the student is the focus of educational institution. This way, the use of softwares of this nature can aid the development of critical thinking and the learning to learn process, contributing for dealing with intellectuals purposes with would be difficultly possible in there best forms without the use of the computer.Dissertação (Mestrado)Este trabalho tem como objetivo desenvolver um ambiente computacional interativo, concebido para auxiliar o projeto geométrico de estradas de rodagem, uma vez que a utilização de softwares educacionais no ambiente de ensino-aprendizagem tem sido cada vez mais frequente em todos os níveis da educação. Para tanto, foi feita uma pesquisa, envolvendo os conceitos do processo de aprendizagem, isto é, os paradigmas educacionais, a ergonomia de Interface Homem/Máquina e seu envolvimento pedagógico. Foi escolhido um público alvo, o curso de Engenharia Civil, com a finalidade de elaborar os cálculos envolvidos no projeto geométrico de estradas, e a fusão dessas informações convergiu para a elaboração do sistema interativo, gerando uma rica fonte de formação de conhecimento. O enfoque deste trabalho está centrado em duas propriedades, a saber, uma de caráter ergonômico, usabilidade, e outra de carater pedagógico, aprendizagem, possibilitando o aprendizado do sistema, bem como o aprendizado no sistema. Assim sendo, foi concebido um simulador para atender aos módulos instrucionais, indicando que há integração entre os critérios de maior conformidade em usabilidade e os critérios de aprendizagem definidos para validar a qualidade pedagógica do software. O processo ensino-aprendizagem deve priorizar o aprendizado dos alunos sobre a forma do ensino de seus professores, pois a instituição educacional, existe em função do aluno, devendo este ser o foco principal. Deste modo, a utilização de softwares desta natureza pode auxiliar o desenvolvimento do pensar crítico e do aprender a aprender nos alunos, podendo contribuir para tratar de propostas intelectuais que dificilmente seriam possíveis de serem criadas nas suas melhores formas sem a utilização do computador

Predictive Controller Based on Paraconsistent Annotated Logic for Synchronous Generator Excitation Control

This study presents a new Model Predictive Controller (MPC), built with algorithms based on Paraconsistent Annotated Logic (PAL), with application examples in the excitation control of a synchronous generator. PAL is a non-classical evidential and propositional logic that is associated with a Hasse lattice, and which presents the property of accepting the contradiction in its foundations. In this research, the algorithm was constructed with a version of the PAL that works with two information signals in the degrees of evidence format and, therefore, is called Paraconsistent Annotated Logic with annotation of two values (PAL2v). For the validation of the algorithmic structure, the computational tool MATLAB® Release 2012b, The MathWorks, Inc., Natick, MA, United States was used. Simulations were performed which compared the results obtained with PPC-PAL2v to those obtained in essays with the AVR (Automatic Voltage Regulator) controls in conjunction with the PSS (Power System Stabilizer) and the conventional MPC of fixed weights. The comparative results showed the PPC-PAL2v to display superior performance in the action of the excitation control of the synchronous generator, with a great efficiency in response to small signals

Process of Learning from Demonstration with Paraconsistent Artificial Neural Cells for Application in Linear Cartesian Robots

Paraconsistent Annotated Logic (PAL) is a type of non-classical logic based on concepts that allow, under certain conditions, for one to accept contradictions without invalidating conclusions. The Paraconsistent Artificial Neural Cell of Learning (lPANCell) algorithm was created from PAL-based equations. With its procedures for learning discrete patterns being represented by values contained in the closed interval between 0 and 1, the lPANCell algorithm presents responses similar to those of nonlinear dynamical systems. In this work, several tests were carried out to validate the operation of the lPANCell algorithm in a learning from demonstration (LfD) framework applied to a linear Cartesian robot (gantry robot), which was moving rectangular metallic workpieces. For the LfD process used in the teaching of trajectories in the x and y axes of the linear Cartesian robot, a Paraconsistent Artificial Neural Network (lPANnet) was built, which was composed of eight lPANCells. The results showed that lPANnet has dynamic properties with a robustness to disturbances, both in the learning process by demonstration, as well as in the imitation process. Based on this work, paraconsistent artificial neural networks of a greater complexity, which are composed of lPANCells, can be formed. This study will provide a strong contribution to research regarding learning from demonstration frameworks being applied in robotics