OPTIMAL AUTOMATIC CONTROL ALGORITHMS FOR ROBOTIC PLATFORMS ENSURING HIGH PERFORMANCE AND RELIABLE OPERATION

Abstract

The article presents a study of contemporary optimal automatic control algorithms for robotic platforms, guaranteeing their high performance, adaptability, and reliability. The main modes of mobile robot locomotion, such as wheeled, tracked, and multi-legged designs, are analyzed. The advantages and disadvantages of each approach are described from the perspective of enhancing energy efficiency and maneuverability in complex operating conditions. Particular attention is paid to the development of adaptive control algorithms that allow the platform to change its motion parameters in response to environmental conditions. To enhance the system's adaptability, the use of linear quadratic regulators, as well as fuzzy controllers for ensuring precise balancing and motion stabilization, is proposed. Algorithmic solutions for automatic control of the platform's motion parameters in rough terrain and the possibility of dynamic reconfiguration of movement routes are presented. The research shows that the use of adaptive algorithms allows for a significant increase in the productivity of robotic platforms, a reduction in the risk of tipping, and guaranteed stable operation even in highly variable environmental conditions. The proposed approach can be used to create a new generation of autonomous systems capable of effectively solving navigation and motion tasks in real-time.