Fuzzy Control and Automatic Learning
0
2023-2024
02042739
Robotics, Control and Systems
Portuguese
English
Face-to-face
6.0
Elective
2nd Cycle Studies - Mestrado
Recommended Prerequisites
Control Systems; Digital Control
Teaching Methods
Theoretical classes of magisterial type with detailed presentation, using audiovisual means, of the concepts, principles, theories, and methodologies, and with the presentation of illustrative and application examples.
Practical laboratory classes, supervised by a professor: in these classes, some time is dedicated to the presentation of topics relevant to the laboratory works; And the rest of the time is dedicated to the development of laboratory works which require the application and combination of different concepts.
Learning Outcomes
Acquire the competencies required to have knowledge and apply the fundamental concepts concerning fuzzy systems and neural networks, as well as analyze, understand and design fuzzy control systems, and systems based on neural networks. Acquire competencies required to have knowledge and apply fundamental concepts concerning to computational learning.
Acquiring competencies in analysis and synthesis, critical reasoning, problem solving, autonomous learning, practical application of theoretical knowledge, adaptivity to new situations.
Work Placement(s)
NoSyllabus
Fuzzy logic. Fuzzy Systems. Knowledge bases, rules. Fuzzy inference. Automatic learning. Fuzzy controllers, and learning methods for their synthesis and automatic calibration. Fuzzy supervisory control. Neural networks and neural network architectures. Learning with neural networks. Control with neural networks. Integration of fuzzy systems and neural networks, neuro-fuzzy controller.
Head Lecturer(s)
Rui Alexandre de Matos Araújo
Assessment Methods
Assessment
Exam: 50.0%
Laboratory work or Field work: 50.0%
Bibliography
• Wang, L.-X. (1997) – A Course in Fuzzy Systems and Control, Prentice-Hall.
• Haykin, S. (1999) – Neural Networks: A Comprehensive Foundation, 2nd Edition, Prentice-Hall.
• Haykin, S. (2009) – Neural Networks and Learning Machines, 3rd Edition, Prentice-Hall.
• Araújo, R. (2015) – Controlo Difuso e Aprendizagem [Apontamentos], Departamento de Engenharia Electrotécnica e de Computadores, Faculdade de Ciências e Tecnologia da Universidade de Coimbra.
• Araújo, R. (2015) – Controlo Difuso e Aprendizagem: Exercícios e Soluções, Departamento de Engenharia Electrotécnica e de Computadores, Faculdade de Ciências e Tecnologia da Universidade de Coimbra.
• Lin, C.-T., Lee, C.S.G. (1997) – Neural Fuzzy Systems - A Neuro-Fuzzy Synergism to Intelligent Systems, Prentice-Hall.
• Babuska, R. (1998) – Fuzzy Modeling for Control, Kluwer Academic Publishers.
• Krose, B., Smagt, P.V.D. (1996) – An Introduction to Neural Networks, The University of Amsterdam.