AI Article Synopsis
- A weighted multiple model adaptive boundary control scheme is designed for a flexible manipulator facing significant parameter uncertainties.
- It involves creating a distributed parameter model using partial differential equations to represent the manipulator, and local boundary controllers are developed to manage its movement and reduce vibrations based on Lyapunov stability theory.
- The strategy incorporates an improved weighting algorithm and demonstrates stability through virtual equivalent system theory, with numerical simulations confirming its effectiveness.
Article Abstract
In this article, a weighted multiple model adaptive boundary control scheme is proposed for a flexible manipulator with unknown large parameter uncertainties. First, the uncertainties are approximatively covered by a finite number of constant models. Second, based on Euler-Bernoulli beam theory and Hamilton principle, the distributed parameter model of the flexible manipulator is constructed in terms of partial differential equation for each local constant model. Correspondingly, local boundary controllers are designed to control the manipulator movement and suppress its vibration for each partial differential equation model, which are based on Lyapunov stability theory. Then, a novel weighted multiple model adaptive control strategy is developed based on an improved weighting algorithm. The stability of the overall closed-loop system is ensured by virtual equivalent system theory. Finally, numerical simulations are provided to illustrate the feasibility and effectiveness of the proposed control strategy.
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Source |
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10452818 | PMC |
| http://dx.doi.org/10.1177/0036850419886468 | DOI Listing |
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