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Neuroadaptive Distributed Sliding Mode Formation Control of UAVs: A More Simple Approach

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  • Intelligent Control and Applications
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Abstract

In this research article, a novel distributed neuroadaptive sliding mode control (SMC) algorithm has been developed for three-dimensional (3-D) formation control of a swarm of unmanned aerial vehicles (UAVs). The UAVs (all identical) track a virtual leader. A sliding mode and a novel robust controller, based on classical SMC, have been conceptualised and developed, which shape the formation and suppress disturbances effectively. Radial basis function neural networks (RBFNNs) have been employed for the function approximation of external disturbances and the generation of the robust control signal. An adaptive law has been proposed for tuning the weights of the neural networks online. The unique feature of the developed algorithm has been its mathematical simplicity and low complexity in implementation as compared to current algorithms. Furthermore, the finite time for formation (i.e., the error convergence time) can be controlled by varying the robust controller gain. A low-pass filter has been implemented, which clears the chattering and oscillations from the control signal. Both time-varying and time-invariant formations have been achieved. The Lyapunov stability analysis proves the overall stability. Numerical simulations show the validity of the proposed algorithm. The proposed algorithm has been tested in a Gazebo simulation environment for the time-invariant case. The Gazebo simulation results confirm the validity of the proposed algorithm. A comparison of control performance indices with a recent work of similar nature yields superior results.

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Authors and Affiliations

  1. Advanced Technology Development Centre, Indian Institute of Technology, Kharagpur, 721302, India

    Nabarun Sarkar

  2. Electrical Engineering Department, Indian Institute of Technology, Kharagpur, 721302, India

    Alok Kanti Deb

Authors
  1. Nabarun Sarkar
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Correspondence to Nabarun Sarkar.

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The authors would like to express their sincere thanks to the Editor and the anonymous Reviewers for their constructive comments, which have helped to improve the overall quality of the manuscript.

Nabarun Sarkar received his B.E. (Hons) degree in electrical engineering from Jadavpur University, Jadavpur, India and an M.Tech degree in electrical engineering from Indian Institute of Technology Kharagpur, Kharagpur, India in 1995 and 2015, respectively. Currently, he is pursuing a Ph.D. degree in control systems engineering from the Indian Institute of Technology Kharagpur, Kharagpur, India. His research interests include formation control, nonlinear control, adaptive control, and computational intelligence.

Alok Kanti Deb received his B.E. (Hons) degree in electrical engineering from the Bengal Engineering College, Calcutta University, Howrah, India and his M.Tech (control engineering and instrumentation) and Ph.D. degrees in electrical engineering from Indian Institute of Technology Delhi, Delhi, India in 1994, 1999, and 2006, respectively. He is currently a Professor with the Department of Electrical Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India. His research interests include embedded systems, control systems engineering, estimation of signals and systems, computational intelligence, and automotive diagnostics.

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Sarkar, N., Deb, A.K. Neuroadaptive Distributed Sliding Mode Formation Control of UAVs: A More Simple Approach. Int. J. Control Autom. Syst. 21, 3470–3483 (2023). https://doi.org/10.1007/s12555-022-0774-4

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  • DOI: https://doi.org/10.1007/s12555-022-0774-4

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