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This study aims to promote the anti-disturbance and tracking accuracy performance of the servo systems, in which a modified active disturbance rejection control (MADRC) scheme is proposed.

An adaptive radial basis function (ARBF) neural network is utilized to estimate and compensate dominant friction torque disturbance, and a parallel high-gain extended state observer (PHESO) is employed to further compensate residual and other uncertain disturbances. This parallel compensation structure reduces the burden of single ESO and improves the response speed of permanent magnet synchronous motor (PMSM) to hybrid disturbances. Moreover, the sliding mode control (SMC) rate is introduced to design an adaptive update law of ARBF.

Simulation and experimental results show that as compared to conventional ADRC and SMC algorithms, the position tracking error is only 2.3% and the average estimation error of the total disturbances is only 1.4% in the proposed MADRC algorithm.

The disturbance parallel estimation structure proposed in MADRC algorithm is proved to significantly improve the performance of anti-disturbance and tracking accuracy.

Most research on sustainable tourism has been devoted to understanding the determinants of tourists' sustainable behavior on a unidimensional construct, overlooking the importance of behavioral costs in sustainable travel behavior. To shed light on this issue, this study aims to quantitatively differentiate sustainable travel behaviors based on behavioral costs and to examine the impact of psychological factors on both low-cost and high-cost sustainable travel behaviors.

A survey of 470 tourists used Rasch analysis to measure the behavioral costs associated with sustainable travel behavior and partial least squares structural equation modeling (PLS-SEM) to test hypotheses.

The results indicate that the value-identity-personal norm model explains more variance in low-cost sustainable travel behaviors than in high-cost sustainable travel behaviors. This supports the central tenet of the low-cost hypothesis and also suggests that values and self-identity factors have a stronger influence on low-cost sustainable travel behavior. However, personal norms have a stronger influence on high-cost behaviors.

This research highlights the importance for tourism and destination managers to distinguish between different categories of sustainable travel behavior and to analyze their determinants separately. This allows for the development of tailored messages for specific groups of tourists based on the psychological drivers of sustainable travel behavior.

This study provides insights into the determinants of sustainable travel behaviors with different behavioral costs and highlights the importance of analyzing different categories of behaviors separately.