Adaptive Fuzzy-Region-Based Control of Euler–Lagrange Systems With Kinematically Singular Configurations

Singularity issue has long been a concern of the task-space control design for Euler-Lagrange systems. In classical task-space controls, robots are often assumed to operate in the task space, where singularities do not exist. Such an assumption limits their potential applications in various workspaces. To address the potential singularity issue associated with Euler-Lagrange systems, this article proposes an adaptive fuzzy-region-based control for Euler-Lagrange systems with kinematically singular configurations. Singular regions are described by the potential energy function. The proposed controller includes a joint-space control, which is active when the system approaches singular regions, and a task-space control, which is used to track the desired trajectory. Therefore, the system can smoothly transit from singular regions to nonsingular regions or can achieve singularity avoidance during the tracking task. In order to achieve singularity avoidance while reducing control effort, the coefficients of the potential energy function are adjusted dynamically based on the designed fuzzy system. Rigorous analysis shows that singularity issues can be properly handled, and the asymptotic stability of the system is ensured. Experiments are conducted to demonstrate the effectiveness of the proposed controller.