This paper introduces a laboratory approach for teaching and learning an Intelligent Control course delivered to Automation andIndustrial Electronics Engineering students. It integrates methods from Control Theory and Artificial Intelligence. Students initiallydevelop a simulated plant controller using the Matlab fuzzy toolbox and the Simulink program. They then apply their design tointerconnected tanks in an actual plant. Other experiments include the expert control of an elevator panel using the CLIPS shelland Linux in real time. This is complemented by the design and implementation of a Neural Network for the identification of aproposed plant. A survey of students’ opinion about the approach and the impact of the approach to learning were assessed.
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