Title:

Intelligent Controllers

Code:QA5
Ac.Year:ukončen 2002/2003
Sem:Winter
Language of Instruction:Czech
Completion:examination (verbal)
Type of
instruction:
Hour/semLecturesSeminar
Exercises
Laboratory
Exercises
Computer
Exercises
Other
Hours:390000
 ExamsTestsExercisesLaboratoriesOther
Points:1000000
Guarantor:Pivoňka Petr, prof. Ing., CSc. (DAME)
Lecturer:Pivoňka Petr, prof. Ing., CSc. (DAME)
Faculty:Faculty of Electrical Engineering and Communication BUT
Department:Department of Control and Instrumentation FEEC BUT
 
Learning objectives:
  Critical practical view and comparative study on most used methods of design and realisation classical, modern and control algorithms with artificial intelligence.
Description:
  Some problems that face us during process control. PID controller as a basic reference controller. Settings and realization of classical industrial controllers. Adaptive, self tuning and heuristic controllers. Adaptive control algorithms based on discrete identification. Typical problems arising during adaptive control. The controllers with artificial intelligence. Introduction into fuzzy logic. Fuzzy controllers. Introduction into neural nets. Neural controllers. Implementation of intelligent controllers in real processes. Example of control of complex process.
Learning outcomes and competencies:
  Course absolvent should be an able to design, to realisation, adjust, comparison and development new classical control algorithms and control algorithms with principles of artificial intelligence.
Syllabus of lectures:
 
  1. Physical background of control.
  2. Design and realisation of continuous PID controllers. Different types of PID controllers, realisation, setting of parameters, comparison, anti-windup and switching between algorithms.
  3. Design and realisation of discrete analogy of continuous PID algorithms.
  4. Philosophy of the process identification and design of controller's algorithm.
  5. Optimum settings of controller's parameters, adaptive controllers, self tuning controllers, specific problems of adaptive control.
  6. Dead beat controllers, state controllers.
  7. Specific problems of optimal control.
  8. Specific problems of predictive control.
  9. Specific problems of MIMO control.
  10. Artificial intelligence in controls algorithms. Fuzzy SISO and MISO controllers.
  11. Artificial neural networks.
  12. Identification with neural networks.
  13. Neural controllers.
 

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