Advanced Intelligent Control and its applications in robotic systems is a result of the needsofimproving the “intelligence” of robotic systems, towardscombining the intelligent behavior with elements of reasoning, learning as well as environment adaptation. The aim of the course is to present, analyze and utilizevarious models and methods of Computational Intelligence,consisting of various research topics related to Artificial Neural Networks, Deep Learning, Fuzzy Systems, Deep Neuro-Fuzzy Networks, Evolutionary Algorithms and Expert Systems.In this course, students will become familiar with models and the theory of Computational Intelligence, as well as with advanced information technologies applied in the field of industry, unit production and transport.

• Robotic Systems: Robot arms (description and analysis of kinematics, orbit design and programming), Mobile robots, (motion analysis, mapping and orbital design for an industrial environment which incorporates obstacles, specifications and optimization criteria), Simulation of robotic systems
• Fuzzy control: Fuzzy Systems and Fuzzy Controllers. Practical application of Fuzzy Systems
• Neural Networks: training, classification and control, practical application of neural networks in optimization problems
• Evolutionary Computing – Systems Optimization: Fundamental terminology of evolutionary computing, Combinatorial Optimization Problems, Genetic Algorithms, Structure and Operation, System Design and Applications of Optimization

This course is using project-based assessment. Students are asked to complete a project on the design and implementation of application (100%) on the following topics:

• Robot route design with criterion optimization. Model based design
• Navigation design for self-driven robots using Artificial Intelligence methods
• Applications using a robot arm simulator

• Utilize a range of Computational Intelligence models and techniques, encompassing Artificial Neural Networks, Deep Learning, Fuzzy Systems, Deep Neuro-Fuzzy Networks, Evolutionary Algorithms, and Expert Systems, for addressing intricate challenges in robotic systems and diverse domains.
• Examine the principles and theory of Computational Intelligence to gain insights into the functioning of intelligent control systems, highlighting their capacity for reasoning, learning, and adapting to diverse environments.
• Create sophisticated control strategies that incorporate aspects of reasoning, learning, and adaptation, demonstrating the capacity to craft intelligent robotic systems and other applications.
• Apply cutting-edge information technologies within the realms of industry, unit production, and transportation, showcasing practical competencies in implementing Computational Intelligence in real-world situations.5. **Evaluate System Performance**: Evaluate the performance of intelligent control systems using Computational Intelligence, quantifying their effectiveness in achieving tasks and adapting to changing conditions.
• Employ the knowledge acquired in the course to tackle intricate problems and confront challenges in the realm of intelligent control, underscoring the significance of Computational Intelligence in contemporary industry and technology.