Intelligent control


Study of inteligent control techniques, both theoreticaly and applied. Starting by introducing concepts on linear dynamic systems identification and adaptive pole placement control, followed by the use of artifitial neural networks and fuzzy logics as means to approximate nonlinear dynamics. The core of this course is the development of neural and fuzzy controllers. 

General characterization





Responsible teacher

Paulo José Carrilho de Sousa Gil


Weekly - 4

Total - 62

Teaching language



Control theory and Computer control systems.


Main references 

  • Identification and Adaptive Control, Paulo Gil, 2002 (in portuguese)

Additional references

  • System Identification, Lennart Ljung, 1987
  • System Identification and Control Design, I. Landau, 1990
  • Neural Network Design, M. Hagan, 1996
  • Neuro-Fuzzy and Soft Computing, Jang, Sun e Mizutani, 1995

Teaching method

The teaching, supported in the use of multimedia projections and e-learning methods (i.e., the use of the Moodle program), will include theoretical and practical classes grounded in the theoretical and application of concepts.

Evaluation method

The course assessment comprises two components: Lab. work ((TG1.1 + TG1.2 + TG1.3)) + two quizzes.

The CI grade is given by:

NP = (TG1.1 + TG1.2 + TG1.3)/3

Grade Normal=  NP*0.4/3 + (MT 1 + MT 2)*0.3;

Grade Exam=  NP*0.4/3 + Exam*0.6.

Required a minimum attendance of 75% in practical classes and minimum of 9.5 out of 20 in all components.

Subject matter

Linear Systems Identification: Problem; The identification process; Linear time invariant models; Parameter estimation: least squares; Model validation; RLS.

 Adaptive Control: Functional models; Pole placement.

 Artificial Neural Networks: The neuron; Activation functions; Proactive multi-layer networks; Approximation properties; Supervised training in multi-layer networks ; Generalization and validation; Neural control architectures.

 Fuzzy Control: Fuzzy systems fundamentals; Defuzzification of variables; Inference with linguistic variables; Defuzzification of linguistic variables; Fuzzy control design.


Programs where the course is taught: