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A Gradient Dynamics-Based Singularity Avoidance Method for Backstepping Control of Underactuated TORA Systems
A Gradient Dynamics-Based Singularity Avoidance Method for Backstepping Control of Underactuated TORA Systems
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A Gradient Dynamics-Based Singularity Avoidance Method for Backstepping Control of Underactuated TORA Systems
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A Gradient Dynamics-Based Singularity Avoidance Method for Backstepping Control of Underactuated TORA Systems
A Gradient Dynamics-Based Singularity Avoidance Method for Backstepping Control of Underactuated TORA Systems

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A Gradient Dynamics-Based Singularity Avoidance Method for Backstepping Control of Underactuated TORA Systems
A Gradient Dynamics-Based Singularity Avoidance Method for Backstepping Control of Underactuated TORA Systems
Journal Article

A Gradient Dynamics-Based Singularity Avoidance Method for Backstepping Control of Underactuated TORA Systems

2024
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Overview
In this paper, a gradient dynamics-based control method is proposed to directly tackle the singularity problem in the backstepping control design of the TORA system. This method is founded upon the construction of an energy-like positive function, which includes an auxiliary variable in terms of the intermediate virtual control law. On this basis, a gradient dynamics is created to obtain a new virtual control command, which is capable of making the auxiliary variable gradually approach zero, thereby mitigating the issue of division by zero. The core innovation is the integration of the gradient dynamics into the recursive backstepping design to overcome the singularity problem and stabilize the system at the equilibrium quickly. In addition, it rigorously proves that all the signals in the closed-loop control system are uniformly ultimately bounded, and the tracking errors converge to a small neighborhood around zero through a Lyapunov-based stability analysis. Comparative simulations demonstrate that the proposed approach not only avoids the singularity issue, but also achieves a better transient performance over other methods.