Faculty of Information Technology, BUT

Course details

Intelligent Controllers

QA5 Acad. year 2003/2004 Winter semester

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.

Guarantor

Language of instruction

Czech

Completion

Examination (oral)

Time span

39 hrs lectures

Assessment points

100 exam

Department

Lecturer

Subject specific learning outcomes and competences

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.

Learning objectives

Critical practical view and comparative study on most used methods of design and realisation classical, modern and control algorithms with artificial intelligence.

Syllabus of lectures

  • Physical background of control.
  • Design and realisation of continuous PID controllers. Different types of PID controllers, realisation, setting of parameters, comparison, anti-windup and switching between algorithms.
  • Design and realisation of discrete analogy of continuous PID algorithms.
  • Philosophy of the process identification and design of controller's algorithm.
  • Optimum settings of controller's parameters, adaptive controllers, self tuning controllers, specific problems of adaptive control.
  • Dead beat controllers, state controllers.
  • Specific problems of optimal control.
  • Specific problems of predictive control.
  • Specific problems of MIMO control.
  • Artificial intelligence in controls algorithms. Fuzzy SISO and MISO controllers.
  • Artificial neural networks.
  • Identification with neural networks.
  • Neural controllers.
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