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This paper aims to propose a hybrid force/position controller based on the adaptive variable impedance.

First, the working space is divided into a force control subspace and a position subspace, the force control subspace adopts the position impedance control strategy. At the same time, the contact force model between the robot and the surface is analyzed in this space. Second, based on the traditional position impedance, the model reference adaptive control is introduced to provide an accurate reference position for the impedance controller. Then, the BP neural network is used to adjust the impedance parameters online.

The experimental results show that compared with the traditional PI control method, the proposed method has a higher flexibility, the dynamic response accommodation time is reduced by 7.688 s and the steady-state error is reduced by 30.531%. The overshoot of the contact force between the end of robot and the workpiece is reduced by 34.325% comparing with the fixed impedance control method.

The proposed control method compares with a hybrid force/position based on PI control method and a position fixed impedance control method by simulation and experiment.

The adaptive variable impedance control method improves accuracy of force tracking and solves the problem of the large surfaces with robot grinding often over-polished at the protrusion and under-polished at the concave.

This study aims to optimize electrical systems represented by ordinary differential equations and events, using their frequency spectrum is an important purpose for designers, especially to calculate harmonics.

This paper presents a methodology to achieve this, by using a gradient-based optimization algorithm. The paper proposes to use a time simulation of the electrical system, and then to compute its frequency spectrum in the optimization loop.

The paper shows how to proceed efficiently to compute the frequency spectrum of an electrical system to include it in an optimization loop. Derivatives of the frequency spectrum such as the optimization inputs can also be calculated. This is possible even if the sized system behavior cannot be defined a priori, e.g. when there are static converters or electrical devices with natural switching.

Using an efficient sequential quadratic programming optimizer, automatic differentiation is used to compute the model gradients. Frequency spectrum derivatives with respect to the optimization inputs are calculated by an analytical formula. The methodology uses a “white-box” approach so that automatic differentiation and the differential equations simulator can be used, unlike most state-of-the-art simulators.

In this paper, a new front end converter (FEC) topology has been proposed for the switched reluctance (SR) motor drive. This study aims to present the performance analysis of FEC-based SR motor drive using various types of control schemes like conventional proportional integral (PI) controller, fuzzy logic controller (FLC) and fuzzy-tuned proportional integral controller (Fuzzy-PI).

The proposed FEC-based SR motor drive with various control strategies is derived for the torque ripple minimization and speed control.

The steady state and the dynamic response of the FEC-based SR motor drive are analyzed using three different controllers under change in speed and loading conditions. The Fuzzy-PI-based control scheme improves the dynamic response of the system when compared with the FLC and the conventional PI controller.

The hardware prototype has been implemented for the FEC-based SR motor drive by using the Xilinx SPARTAN 6 FPGA processor. The experimental verification has been conducted and the results have been measured under steady state and dynamic conditions.

The purpose of this paper is to examine the hotel growth model including hotel brand, culture and life cycle phases of the Myrtle Beach, South Carolina, the fastest growing tourism destination in the United States.

Culture reflecting consuming behaviour of low-context innovators and high-context imitators is measured by the price elasticity of demand (PED). Hotel brand reflecting guests’ hotel class is measured by the income elasticity of demand. Autoregressive distributed lag has been conducted on the Smith Travel Research data in 33 years (1989–2022) to determine the relationship among hotel brand, culture and life cycles.

Skilled labour is the key to make hotels grow. Therefore, increase room rates when hotels possess skilled professionals and decrease room rates when hotels have no skilled professionals. During the rejuvenation in Myrtle Beach (1999–2003), hoteliers increased room rates for innovators due to skilled professionals to increase revenue. Otherwise, a decrease in room rates due to lack of skilled professionals would lead to increase revenue.

(1) Although Myrtle Beach is one of the fastest growing tourism destinations in the US, it has a relatively small geographic area relative to the country. (2) Data cover over one tourist life cycle, so the time span is relatively short. Hoteliers can forecast the number of guests in different culture by changing room rates.

To optimize revenue, hoteliers can select skilled labour in professional design hotel brands which could make an increase in demand for leisure transient guests no matter what room rates increase after COVID-19 pandemic.

The study has considered the applied ethical processes regarding revenue management that would maximize both revenue and customer satisfaction when it set up an increase in room rates to compensate for professional hotel room design or it decreases room rates for low-income imitators in exploration and development.

This research highlights that (1) skilled design in the luxury hotel brand is the key for the hotel growth and (2) there is a steady state of the growth model in the destination life cycle.

This paper aims to describe a modelling and solving methodology of a (static converter–electric motor–control) system for its sizing by optimization, considering the dynamic thermal heating of the machine.

The electrical drive sizing model is composed of two simulators (electrical and thermal) that are co-simulated with a master−slave relationship for the time step management. The computation is stopped according to simulation criteria.

This paper details a methodology to represent and size an electrical drive using a multiphysics and multidynamics approach. The thermal simulator is the master and calls the electrical system simulator at a fixed exchange time step. The two simulators use a dedicated dynamic time solver with adaptive time step and event management. The simulation automatically stops on pre-established criteria, avoiding useless simulations.

This paper aims to present a generic methodology for the sizing by optimization of electrical drives with a multiphysics approach, so the precision and computation time highly depend on the modelling method of each components. A genetic multiobjective optimization algorithm is used.

The methodology can be applied to size electrical drives operating in a thermally limited zone. The power electronics converter and electrical machine can be easily adapted by modifying their sub-model, without impacting the global model and simulation principle.

The approach enables to compute a maximum operating duration before reaching thermal limits and to use it as an optimization constraint. These system considerations allow to over constrain the electrical machine, enabling to size a smaller machine while guaranteeing the same output performances.

Transient response of continuous composite material (CCM) fin made of high thermally conductive composite material is presented. The continuously varying effective properties of composite material such as thermal conductivity, heat capacity and density have been modelled using the Mori-Tanaka homogenization theory and rule of mixture. Additionally, temperature dependency of thermal conductivity, heat generation (composite materials) and convection coefficient (fluid properties) have also been incorporated. Different base boundary conditions are addressed such as oscillating heat flow, oscillating temperature, step-changing heat flow and step-changing temperature. At the other boundary, the fin is assumed to have a convective tip.

Lattice Boltzmann method is implemented using an in-house source code for obtaining the numerical solution of typical non-linear heat balance equation of the aforementioned problem under various transient base boundary conditions.

The effects of various thermal parameters such as material diffusivity ratio and conductivity ratio, area ratio and Biot number on transient response of fin and temperature distribution of fins are studied and interpreted. The heat transfer rate and time for attainment of steady state temperature of metal matrix composite (MMC) fin are found to be proportionally dependent on their diffusivity ratio. Additionally for higher values of area ratio and biot number, MMC fins are reported to dissipate the heat more efficiently in comparision to homogeneous fins in terms of time required to attain the steady state and surface temperature.

Response of transient fin associated with advanced class of material can facilitates the practicing engineers for designing high-performance and/or miniaturized thermal management devices as used in electronic packaging industries.

Studies of composite fin consisting of laminating second layer of material over the first layer have been reported previously, however transient response of CCM fin fabricated by continuously varying the volume fraction of two materials along the fin length has not been reported till date. Such material finds its application in thermal management and electronic packaging industries. Results are plotted in form of a graph for different application-wise material combinations that have not been reported earlier, and it can be treated as design data.

The purpose of this study is to stabilize the rotating speed of the permanent magnet direct current (PMDC) motor driven by a DC-DC boost converter under mismatched disturbances (i.e.) under varying load circumstances like constant, frictional, fan type, propeller and undefined torques.

This manuscript proposes a higher order sliding mode control to elevate the dynamic behavior of the speed controller and the robustness of the PMDC motor. A second order classical sliding surface and proportional-integral-derivative sliding surface (PIDSS) are designed and compared.

For the boost converter with PMDC motor, both simulation and experimentation are exploited. The prototype is built for an 18 W PMDC motor with field programmable gate arrays. The suggested sliding mode with second order improves the robustness of the arrangement under disturbances with a wide range of control. Both the simulation and experimental setup shows satisfactory results.

According to software-generated mathematical design and experimental findings, PIDSS exhibits excellent performance with respect to settling speed, steady-state error and peak overshoot.

The purpose of this study is to provide a highly efficient method to obtain the kinetics of the hydrogen evolution reaction (HER) on metal electrodes in an alkaline solution and to analyze the effect of thiourea addition on HER under the same cathodic overpotential.

A novel method based on hydrogen permeation tests, potentiodynamic polarization tests and electrochemical impedance spectroscopy was put forward to characterize the HER kinetics on metal electrode.

The study found that adding thiourea accelerated the Volmer, Heyrovsky and Tafel reactions associated with HER. In addition, it reduced the hydrogen surface coverage and increased the hydrogen permeation steady-state current density. As a result, thiourea facilitated HER, promoted the diffusion of hydrogen atoms into iron and reduced the number of hydrogen atoms in the adsorbed state.

This work provides novel insights into the influence of thiourea on HER kinetics, demonstrating that thiourea addition can significantly enhance HER efficiency by altering reaction dynamics and promoting hydrogen atom diffusion into iron. This has implications for hydrogen energy applications, cathodic protection and understanding hydrogen embrittlement mechanisms.

This paper aims to investigate the relative translational control for multiple spacecraft formation flying. This paper proposes an engineering-friendly, structurally simple, fast and model-free control algorithm.

This paper proposes a tanh-type self-learning control (SLC) approach with variable learning intensity (VLI) to guarantee global convergence of the tracking error. This control algorithm utilizes the controller's previous control information in addition to the current system state information and avoids complicating the control structure.

The proposed approach is model-free and can obtain the control law without accurate modeling of the spacecraft formation dynamics. The tanh function can tune the magnitude of the learning intensity to reduce the control saturation behavior when the tracking error is large.

This algorithm is model-free, robust to perturbations such as disturbances and system uncertainties, and has a simple structure that is very conducive to engineering applications.

This paper verified the control performance of the proposed algorithm for spacecraft formation in the presence of disturbances by simulation and achieved high steady-state accuracy and response speed over comparisons.

The main objective of the present investigation is to develop a novel efficient stochastic model for availability optimization of reverse osmosis machine system (ROMS) for water purification under the concepts of exponentially distributed decision variables and various redundancy strategies at the component level.

ROMS is a complex framework configured in a series structure using six subsystems. Initially, a state transition diagram is developed and Chapman–Kolmogorov differential-difference equations are derived using Markov birth death process. The steady-state availability of the ROMS is derived for a particular case. The impact of variation in failure and repair rates measured on availability. Furthermore, an effort is made to predict the optimal availability of the ROMS system using the metaheuristic algorithms, namely, dragonfly algorithm (DA), grasshopper optimization algorithm (GOA) and whale optimization algorithm (WOA).

It is observed that the ROMS system predicts optimal availability of 0.999926 after five iterations with a population size of 300 by the WOA. The findings of this study are significant for reliability engineers as well as for maintenance engineers to ensure the availability of ROMS for water purification.

In the present investigation, a novel stochastic model is developed for ROMS, and metaheuristics algorithms are applied to predict the optimal availability.