Abstract
Subject matter: The study focuses on the control methods for dr20 type robot swarms, specifically on the derivative and integral terminal sliding mode control combined with a nonlinear disturbance observer. The problem of effective swarm control is highly relevant in the current conditions of automation and robotics, especially in the context of performing complex tasks in limited space and in the presence of disturbances. Goal: The development and analysis of a simulation model for the movement of a robot swarm using advanced control methods to ensure system accuracy and stability. The research aims to improve the control methods for robot swarms, enhancing their efficiency and reliability in various operational conditions. Tasks: 1) Develop a simulation model of a robot swarm in the CoppeliaSimEDU environment, considering all necessary parameters for modeling real operating conditions. 2) Implement control algorithms for the leader and followers to maintain the swarm structure and avoid collisions. 3) Conduct a series of experiments to test the effectiveness of the proposed methods, analyzing the results in terms of stability and control accuracy. Methods: Modeling in CoppeliaSimEDU, implementing control algorithms based on derivative and integral terminal sliding mode control, applying a nonlinear disturbance observer to improve system stability. The applied methods allow for the consideration of various disturbances and ensure high control accuracy. Results: he proposed control model allows achieving high following accuracy and collision avoidance even in complex conditions. Experiments have shown that the control methods ensure the stability and accuracy of the robot swarm's movement, reducing the response time to external disturbances. The research results demonstrate that the use of derivative and integral terminal sliding mode control combined with a nonlinear disturbance observer significantly enhances the efficiency of multi-robot systems. Conclusions: The use of advanced control methods significantly improves the efficiency of multi-robot systems, ensuring their reliability and accuracy in real operating conditions. The proposed methods can be applied in various fields where the coordination of a large number of robots is required, including logistics, rescue operations, and environmental monitoring.
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