Barrier function-based adaptive nonsingular terminal sliding mode control technique for a class of disturbed
Saleh Mobayen1, Farhad Bayat2, Sami Ud Din3
1Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan; Department of Electrical Engineering, University of Zanjan, Zanjan, Iran.
This study introduces an adaptive non-singular terminal sliding mode controller (NTSMC) using barrier functions for robust stability in non-linear systems. The controller ensures finite-time convergence and avoids overestimating gains, even with unknown disturbances.
Area of Science:
- Control Systems Engineering
- Non-linear Dynamics
Background:
- Non-linear dynamic systems are susceptible to external disturbances, impacting their stability and performance.
- Existing sliding mode controllers often require knowledge of disturbance bounds and can suffer from chattering or singularity issues.
Purpose of the Study:
- To design an adaptive non-singular terminal sliding mode controller (NTSMC) for robust stability of non-linear systems.
- To ensure finite-time convergence and singularity-free dynamics in the presence of external disturbances.
- To achieve tracking error convergence without overestimating controller gains or prior knowledge of disturbance bounds.
Main Methods:
- Design of an adaptive non-singular terminal sliding mode controller (NTSMC).
- Integration of Barrier Functions (BFs) as an adaptation mechanism for the NTSMC.
- Lyapunov-based stability analysis to guarantee asymptotic convergence of tracking errors.
Main Results:
- The proposed NTSMC achieves robust stability for non-linear dynamic systems under external disturbances.
- Finite-time convergence and singularity-free control are demonstrated.
- Tracking errors converge to a predefined neighborhood of the origin without requiring knowledge of disturbance upper bounds.
Conclusions:
- The adaptive NTSMC with barrier functions provides an effective solution for robust control of non-linear systems.
- The method offers improved performance by avoiding controller gain overestimation and disturbance bound dependency.
- Simulations and experimental results validate the proposed approach's effectiveness.
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