AI Article Synopsis
- The paper discusses a new control algorithm for robotic manipulators that addresses issues like complex structures and uncertainties.
- It utilizes fuzzy set theory to tackle system uncertainties and ensures the system's performance remains stable (uniform boundedness and uniform ultimate boundedness).
- The proposed method has been validated through numerical simulations and experiments, demonstrating its effectiveness in optimizing controller settings.
Article Abstract
As a typically complex mechanical system, robotic manipulator has the characteristics of complex structure, parameter uncertainty and vulnerability to external interference. From the perspective of second-order servo constraints, this paper proposes a robust constraint following control algorithm, which can meet the control requirements of robotic manipulator system under system uncertainty, which is described by fuzzy set theory. It also guarantees the deterministic performance of uniform boundedness (UB) and uniform ultimate boundedness (UUB). The system performance index function based on fuzzy information is established, and by minimizing the system performance index function, the optimization design problem of the controller gain parameter is solved. Numerical simulations and experimental results verify the efficacy of the robust controller and control parameter optimization method.
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| http://dx.doi.org/10.1016/j.isatra.2024.12.041 | DOI Listing |
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