The textbook deals with the simulation of intelligent control systems and knowledge base design technology for fuzzy controllers of unconventional robotic models in the
conditions of uncertainty and imperfect information risk. New models of unconventional robotics as wall climbing robots and aerial unmanned vehicles with robotic manipulators
considered. Detailed functional structure of a knowledge base optimizer based on the soft computing technology introduced. Background of computational intelligence IT
based on soft computing optimizer of knowledge base in smart robotic manipulators and autonomous robots introduced. Soft computing optimizer is the toolkit of deep machine learning SW platform with optimal fuzzy neural network structure. New criteria of control quality based on information-thermodynamic law of stability, controllability and
robustness demonstrated. Interrelations with free energy principle and active inference considered. The practical features of the knowledge base technology for the R & D of
fuzzy controllers with a required level of intelligence in real ill-defined physical control objects discussed. Industrial examples of the effectiveness of the developed computational intelligence toolkit of intelligent robotics and mechatronics described. Application of quantum soft computing in robust intelligent control of smart manipulators in Part III described.
The tool of textbook intended for students, teachers and professionals involved in the design and research management systems in problem-oriented robotic science and technology fields.