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Course Description Course Name : Intelligent Control Systems Course Code : CENG-556 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Spring (16 Weeks) ECTS : 6 Name of Lecturer(s) : Asst.Prof.Dr. RAMAZAN ÇOBAN Learning Outcomes of the Course : Analyzes and designs intelligent control systems Designs control systems according to the predetermined performance specifications. Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : To teach all the students to analyze and design intelligent control systems and to design control systems according to the predetermined performance specifications. Course Contents : Introduction to intelligent control systems. Fuzy logic control. Neural networks control. Evolutionary computation in control system design. Hybrid systems: Neural fuzzy controllers, Genetic fuzzy controllers. Language of Instruction : English Work Place : classroom   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Introduction to intelligent control systems Classical lecturing, question and answer 2 Fuzy logic control Classical lecturing, question and answer 3 Fuzy logic control Classical lecturing, question and answer 4 Fuzy logic control Classical lecturing, question and answer 5 Neural networks control Classical lecturing, question and answer 6 Neural networks control Classical lecturing, question and answer 7 Neural networks control Classical lecturing, question and answer 9 Evolutionary computation in control system design Classical lecturing, question and answer 10 Evolutionary computation in control system design Classical lecturing, question and answer 11 Hybrid systems: Neural fuzzy controllers, Classical lecturing, question and answer 12 Hybrid systems: Neural fuzzy controllers, Classical lecturing, question and answer 13 Hybrid systems: Genetic fuzzy controllers. Classical lecturing, question and answer 14 Hybrid systems: Genetic fuzzy controllers. Classical lecturing, question and answer   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Intelligent Control Systems Using Soft Computing Methodologies - Ali Zilouchian, CRC Press. Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 75     Homeworks/Projects/Others 13 25 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Reaches wide and deep knowledge through scientific research in the field of computer engineering, evaluates, implements, and comments. 5 2 Describes and uses information hidden in limited or missing data in the field of computer engineering by using scientific methods and integrates it with information from various disciplines. 5 3 Follows new and emerging applications of computer engineering profession, if necessary, examines and learns them 5 4 Develops methods and applies innovative approaches in order to formulate and solve problems in computer engineering. 4 5 Proposes new and/or original ideas and methods in the field of computer engineering in developing innovative solutions for designing systems, components or processes. 0 6 Designs and implements analytical modeling and experimental research and solves the complex situations encountered in this process in the field of Computer Engineering 4 7 works in multi disciplinary teams and takes a leading role and responsibility. 3 8 Learns at least one foreign language at the European Language Portfolio B2 level to communicate orally and written 2 9 Presents his/her research findings systematically and clearly in oral and written forms in national and international meetings. 4 10 Describes social and environmental implications of engineering practice. 3 11 Considers social, scientific and ethical values in collection, interpretation and announcement of data. 4 12 Acquires a comprehensive knowledge about methods and tools of computer engineering and their limitations. 5 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 13 3 39     Out of Class Study (Preliminary Work, Practice) 13 4 52 Assesment Related Works     Homeworks, Projects, Others 13 3 39     Mid-term Exams (Written, Oral, etc.) 1 14 14     Final Exam 1 14 14 Total Workload: 158 Total Workload / 25 (h): 6.32 ECTS Credit: 6