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摘要
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In this study, we have undertaken the design and implementation of a pneumatic-driven translational pyramidal manipulator (PTPM) with the primary objective of achieving reliable and precise motion control, even under conditions where the PTPM may be exposed to disturbances arising from coupling effects and internal uncertainties. To achieve this purpose, the ALADRC, an adaptive controller that integrates a linear active disturbance rejection controller (LADRC) with a reduced-order linear extended state observer (RLESO) and a radial basis function neural network optimizer (RFNNO), is presented in this paper. This ALADRC has the following advantages in the view of practical applications: (1) it rejects total disturbances and coupling effect, (2) it reduces the order of the extended state observer, (3) it selects observer gains according to system frequencies, and (4) it optimizes controller gains in real time. Two trajectory tracking experiments and three disturbance rejection experiments were conducted to verify the trajectory tracking and disturbance compensation performance of the designed PTPM, respectively. The experimental results indicated that the PTPM controlled using the ALADRC increased the robustness in external disturbance rejection and provided accurate trajectory tracking. |
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