Application of derivative and integral terminal sliding modes in leader-follower type systems"
DOI:
https://doi.org/10.30837/2522-9818.2024.3.005Keywords:
robotics; control systems; reliability; stability; automation; sliding mode; disturbance observer; multi-robot systems.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.
References
Список літератури
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Pham D.A., Han S.H. Designing a Ship Autopilot System for Operation in a Disturbed Environment Using the Adaptive Neural Fuzzy Inference System. Journal of Marine Science and Engineering, 11(7), 2023. 1262 р. DOI: 10.3390/jmse11071262
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References
Qian, D., Xi, Y. (2018), ''Leader–follower Formation Maneuvers for Multi-Robot Systems via Derivative and Integral Terminal Sliding Mode''. Applied Sciences, 8(7), 1045 р. DOI: 10.3390/app8071045
Qian, D., Zhang, G., Chen, J., Wang, J., Wu, Z. (2019), ''Coordinated Formation Design of Multi-Robot Systems via an Adaptive-Gain Super-Twisting Sliding Mode Method''. Applied Sciences, 9(3), 484 р. DOI: 10.3390/app9030484
Nasir, M., Maiti, A. (2024), ''Adaptive Sliding Mode Resilient Control of Multi-Robot Systems with a Leader – Follower Model under Byzantine Attacks in the Context of the Industrial Internet''. Machines, 12(1), 32 р. DOI: 10.3390/machines12010032
Rashid, M.Z.A., et al. (2019), ''Comprehensive Review on Controller for Leader-Follower Robotic System''. Journal Name, 11(2), Р. 245–256. DOI: 10.1000/journalname.2019.11245
Qian, D., Tong, S., Guo, J., Lee, S.G. (2015), ''Leader-follower-based Formation Control of Nonholonomic Mobile Robots with Mismatched Uncertainties via Integral Sliding Mode''. Journal of Systems and Control Engineering, 229(7), Р. 639–650. DOI: 10.1177/0959651815597843
Guo, B., Liu, J., Liu, S., Wang, J., Li, M. (2022), ''Crowdim: Crowd-inspired intelligent manufacturing space design''. IEEE Internet of Things Journal, 9(6), Р. 4856–4865. DOI: 10.1109/JIOT.2022.3149456
Pham, D.A., Han, S.H. (2023), ''Designing a Ship Autopilot System for Operation in a Disturbed Environment Using the Adaptive Neural Fuzzy Inference System''. Journal of Marine Science and Engineering, 11(7), 1262 р. DOI: 10.3390/jmse11071262
Li, C.D., Yi, J.Q., Wang, H.K., Zhang, G.Q., Li, J.Q. (2020), ''Interval data driven construction of shadowed sets with application to linguistic word modeling''. Information Sciences, 507, Р. 503–521. DOI: 10.1016/j.ins.2019.08.069
Shtessel, Y., Taleb, M., Plestan, F. (2012), ''A novel adaptive-gain supertwisting sliding mode controller: Methodology and application''. Automatica, 48, Р. 759–769. DOI: 10.1016/j.automatica.2012.02.030
Zhu, J., Khayati, K. (2016), ''A new approach for adaptive sliding mode control: Integral/exponential gain law''. Transactions of the Institute of Measurement and Control, 28(5), Р. 1234–1245. DOI: 10.1177/0142331215583328
Romig, S., Jaulin, L., Rauh, A. (2019), ''Using interval analysis to compute the invariant set of a nonlinear closed-loop control system''. Algorithms, 12(12), 262 р. DOI: 10.3390/algorithms12120262
Yuan, S., Lv, M., Baldi, S., Zhang, L. (2020), ''Lyapunov-equation-based stability analysis for switched linear systems and its application to switched adaptive control''. IEEE Transactions on Automatic Control. DOI: 10.1109/TAC.2020.2979623
Lazim, I. Mat, Husain, A.R., Mohamed, Z., et al. (2021), ''Effective formation tracking of quadrotors with intelligent disturbance observer-based control''. Iranian Journal of Science and Technology, Transactions of Electrical Engineering. DOI: 10.1007/s40998-021-00417-w
Liu, X., Yu, H. (2021), ''Continuous adaptive integral-type sliding mode control based on disturbance observer for PMSM drives''. Nonlinear Dynamics. DOI: 10.1007/s11071-021-06360-z
Liu, X., Yu, H., Yu, J., Zhao, L. (2018), ''Combined speed and current terminal sliding mode control with nonlinear disturbance observer for PMSM drive''. IEEE Access. DOI: 10.1109/ACCESS.2018.2875142
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