Intelligent system for marine mobile object trajectory motion control and object classification

Annotation. The relevance of the issue of developing intelligent control systems and classification of dynamic objects is dictated by the fact that in the field of application of artificial intelligence systems a large class of complex objects that require real-time control and operate in a problematic (uncertain) environment has appeared. For example, marine mobile objects (including unmanned ones), deck-based unmanned aerial vehicles, etc. The construction of control systems for these objects using classical control theory does not allow obtaining the required quality of control in real time. In this regard, the paper presents the basic principles of constructing intelligent control systems for complex dynamic processes and classifying objects observed by them using a fuzzy method of representing knowledge. The issues of construction and problems of implementation of logical-linguistic (fuzzy) models of management decision-making in artificial intelligence systems operating in real time are considered. An analysis of modern methods of processing fuzzy information and means of implementing fuzzy control algorithms has been carried out. It is noted that the discrepancy between the structures of modern computing devices and the parallel nature of processing fuzzy information in the process of implementing fuzzy control algorithms does not allow full use of the possibilities of constructing and implementing logical-linguistic models for controlling complex processes and classifying dynamic objects in real time. Generalized structural elements of homogeneous processors are proposed, on the basis of which three-dimensional associative modules of a specialized coprocessor of a bit-parallel operating principle are created, which serves for processing knowledge in the decision-making process, as well as the structure of an intelligent system for controlling the trajectory movement of a marine mobile object and classifying objects based on a fuzzy knowledge base.