Instruments and Systems: Monitoring, Control, and Diagnostics Annotation << Back Overview of Direct Numerical Optimization Methods for Intelligent Control Systems for Unmanned Robotic Devices D.A. GAVRILOV, E.A. TATARINOVA, A.V. LEUS, V.E. BUZDIN, A.A. MERKELOV, A.YU. GORNOV, MURSHID YAZAN, O.A. POTKIN The article presents an overview of direct numerical optimization methods for intelligent control systems for unmanned robotic devices. The history of the development of the direction, methods of studying the problems of nonlinear adaptive control, system modeling in the study of controlled processes with forecasting are considered. With regard to autonomous transport, mobile robots must move in dynamic environments while meeting the specified restrictions. Working algorithms with feedback are needed, capable of quickly responding to changing conditions. The features of problem formulations in terms of nonlinear adaptive control, modern multi-method computing technologies for studying nonlinear adaptive control with prediction are considered: online optimization algorithms using offl ine schedulers and machine learning algorithms based on the use of artificial neural networks of various structures. The experience of developing and implementing an embedded optimal control strategy for autonomous driving applications on a road vehicle is studied. The results of the analysis of technologies used in practice are presented. The use of the considered technologies makes it possible to study the methods of nonlinear adaptive control with prediction for a robotic vehicle. Keywords: direct numerical optimization method, computational technologies, nonlinear adaptive control. DOI: 10.25791/pribor.5.2023.1409 Pp. 24-40.