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The purpose of this paper is to design an output-feedback algorithm based on low-power observer (LPO), robust chattering-free controller and nonlinear disturbance observer (DO) to achieve trajectory tracking of quadrotor in the Cartesian plane.

To achieve trajectory tracking control, firstly the decoupled rotational and translational model of quadrotor are modified by introducing backstepped state-space variables. In the second step, robust integral sliding mode control is designed based on the proportional-integral-derivative (PID) technique. In the third step, a DO is constructed. In next step, the measurable outputs, i.e. rotational and translational state variables, are used to design the LPO. Finally, in the control algorithm all state variables and its rates are replaced with its estimates obtained using the state-observer.

The finding includes output-feedback control (OFC) algorithm designed by using a LPO. A modified backstepping model for rotational and rotational systems is developed prior to the design of integral sliding mode control based on PID technique. Unlike traditional high-gain observers (HGO), this paper used the LPO for state estimation of quadrotor systems to solve the problem of peaking phenomenon in HGO. Furthermore, a nonlinear DO is designed such that it attenuates disturbance with unknown magnitude and frequency. Moreover, a chattering reduction criterion has been introduced to solve the inherited chattering issue of controllers based on sliding mode technique.

This paper presents input and output data-driven model-free control algorithm. That is, only input and output of the quadrotor model are required to achieve the trajectory tracking control. Therefore, for practical implementation, the number of on-board sensor is reduced.

Although extensive research has been done for designing OFC algorithms for quadrotor, LPO has never been implemented for the rotational and translational state estimations of quadrotor. Furthermore, the mathematical model of rotational and translational systems is modified by using backstepped variables followed by the controller designed using PID and integral sliding mode control technique. Moreover, a DO is developed for attenuation of disturbance with unknown bound, magnitude and frequency.

This study aims to examine the influence of team-level green human resource management practices (TGHRM) on team-level green creative behavior (TGCB) through team green psychological climate (TGPC). Additionally, it delves into the moderating effects of ethical leadership (EL) and green culture (GC) on the relationships among team-level GHRM, TGPC and TGCB.

Using a cross-sectional design, data were gathered from hotel teams and were analyzed using the PROCESS model.

The results indicate that TGHRM significantly impacts TGCB via TGPC. Moreover, the study provides partial evidence supporting the moderating roles of EL and GC in the relationships between TGHRM, TGPC and TGCB.

These findings offer valuable insights for managers and practitioners. They highlight the potential to enhance TGCB by implementing GHRM practices, nurturing a TGPC and cultivating both EL and a GC within teams.

This research addresses a gap in the literature, focusing on the effects of TGHRM on TGCB and shedding light on the intertwined social and psychological processes. Further, it broadens the discourse by analyzing the moderating influence of EL and GC in the dynamics between TGHRM, TGPC and TGCB.

Drawing motivation from Lawrence Bossidy's quote and leaning on the conservation of resources (COR) theory, in this study, the authors aim to investigate the role of high-performance work practices (HPWPs) and psychological capital (H.E.R.O) in employee innovative work behavior (EIB).

The study is banked on a hypothetico-deductive approach. The relationships were measured by gathering data from 375 frontline service employees through structural equation modeling.

The study results indicate a positive impact of HPWPs on EIB. Moreover, the association between HPWPs-EIB is mediated by psychological capital (PsyCap).

The current study contributed to the innovation research stream by determining driving forces that encourage employees to exhibit innovative work behaviors.

Employee innovative behavior has become imperative for organizational survival and success in an ever-changing global business environment. Owing to this organizational significance, employee innovative behavior continues to gain burgeoning research attention. Despite the rising scholarly interest in studying employee innovative behavior, there is a dearth of knowledge about how innovation can be fostered at the individual level, particularly among frontline service employees. Hence, to bridge this research gap, the present study intends to analyze the influence of high-performance work practices on employee innovative work behavior, mediated by psychological capital.

The purpose of this study was to develop a correlation between the properties of acrylonitrile butadiene styrene parts 3D printed by material extrusion (MEX) process.

The two MEX parameters and their values have been selected by design of experiment method. Three properties of MEX parts, i.e. strength (tensile and three-point bending), surface roughness and the dimensional accuracy, are studied at different build speeds (35 mm/s, 45 mm/s and 55 mm/s) and the layer heights (0.06 mm, 0.10 mm and 0.15 mm).

The results show that tensile strength and three-point bending strength both increase with the decrease in build speed and the layer height. The artifact selected for dimensional accuracy test shows higher accuracy of the features when 3D printed with 0.06 mm layer height at 35 mm/s build speed as compared to those of higher layer heights and build speeds. The optical images of the 3D-printed specimen reveal that lower build speed and the layer height promote higher inter-layer diffusion that has the effect of strong bonding between the layers and, as a result, higher strength of the specimen. The surface roughness values also have direct relation with the build speed and the layer height.

The whole experiments demonstrate that the part quality, surface roughness and the mechanical strength are correlated and depend on the build speed and the layer height.