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Large optical mirror processing systems (LOMPSs) consist of multiple subrobots, and correlated disturbance terms between these robots often lead to reduced processing accuracy. This abstract introduces a novel approach, the nonlinear subsystem adaptive dispersed fuzzy compensation control (ADFCC) method, aimed at enhancing the precision of LOMPSs.

The ADFCC model for LOMPS is developed through a nonlinear fuzzy adaptive algorithm. This model incorporates control parameters and disturbance terms (such as those arising from the external environment, friction and correlation) between subsystems to facilitate ADFCC. Error analysis is performed using the subsystem output parameters, and the resulting errors are used as feedback for compensation control.

Experimental analysis is conducted, specifically under the commonly used concentric circle processing trajectory in LOMPS. This analysis validates the effectiveness of the control model in enhancing processing accuracy.

The ADFCC strategy is demonstrated to significantly improve the accuracy of LOMPS output, offering a promising solution to the problem of correlated disturbances. This work holds the potential to benefit a wide range of practical applications.

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.

This paper aims to introduce the quasi impedance source inverter (qZSI)-based static compensator (STATCOM), which is incorporated into the hybrid distributed power generation system for enhancement of power quality. The distributed power generation system includes the photovoltaic (PV), wind energy conversion system (WECS) and battery energy storage system.

The WECS is used by the self-excited induction generator (SEIG) and the flywheel energy storage system (FESS). To regulate its terminal voltage and frequency, the SEIG requires adjustable volt-ampere reactive (VAR). A combination of a STATCOM and a fixed condenser bank usually serves to satisfy the VAR demand. The maximum correntropy criterion-based adaptive filter technique (AFT) is proposed to control the qZSI-STATCOM and to guarantee that the voltage at the SEIG terminal is harmonic-free while providing non-linear three-phase and single-phase loads.

The coordinated operation of the suggested voltage control and flywheel control systems ensures that load voltage and frequency are retained in their respective values at very low harmonic distortions regardless of wind speed and load variation. The simulation and experimental studies are carried out under different load conditions to validate the efficiencies of the PV-assisted STATCOM.

To improve system stability and minimize total costs, extra load current sensors can also be avoided. This paper proposes to control the SEIG terminal voltage and harmonic elimination in the standalone WECS systems using maximum correntropy criterion-based AFT with a fuzzy logic controller.

The purpose of this paper is to propose a decision support framework that can be used by decision-makers to identify the most convenient disruption analysis (DA) methods for megaprojects and their stakeholders.

The framework was initially developed by conducting a comprehensive literature review to obtain extensive knowledge about disruption management and megaprojects. Focus group discussion (FGD) sessions with the participation of the construction practitioners were then organized to validate and strengthen the findings of the literature review. Consequently, 17 selection factors were identified and categorized as requirement, ability and outcome. Lastly, the most convenient DA methods for megaprojects were identified by performing integrated fuzzy analytical hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) analysis. Additionally, consistency analysis was also conducted to verify the reliability of the results.

The results revealed that the measured mile method is the most appropriate DA method for megaprojects. In case the measured mile method cannot be adopted due to various technical and contractual reasons, the decision-makers are proposed to consider program analysis, work or trade sampling, earned value analysis and control chart method, respectively. Second, the selection factors such as “Comprehensible analysis procedure,” “Existing knowledge and experience about a particular DA method,” “Ability to resolve greater number of disruption events,” “Ability to resolve complex disruption events,” “Ability to exclude factors that are not under the owner's responsibility” and “General acceptance by practitioners, courts, and arbitration, etc.” were given the top priority by the experts, highlighting the critical aspects of the DA methods.

Disruption claims in megaprojects are very critical for the contractors to compensate for the losses stemming from disruption events. Although the effective use of DA methods maximizes the accuracy and reliability of disruption claims, decision-makers can barely implement these methods adequately since past studies neglect to present extensive knowledge about the most convenient DA methods for megaprojects. Thus, developing a decision support framework for the selection of DA methods, this study is the earliest attempt that examines the mechanisms and inherent differences of DA methods. Additionally, owing to the robustness and versatility of this research approach, the research approach could be replicated also for future studies focusing on other project-based industries since disruption is also a challenging issue for many other industries.

The purpose of this paper is to propose a disruption claim management (DCM) life cycle and a risk management framework to provide comprehensive guidance to construction practitioners for facilitating effective and efficient DCM.

DCM life cycle was initially developed through a focus group discussion (FGD) with the participation of the construction practitioners who have diverse experiences about DCM. The life cycle is comprised of 6 phases and also includes proper reactions of the owners and contractors. Then, 42 risk factors that can impact the deliverables of DCM were identified through a literature review and an additional FGD session. This was then followed by a Fuzzy Analytical Hierarchy Process (FAHP) which was performed to evaluate the importance of each risk factor in terms of the factor's impact on the success of DCM. Additionally, consistency analysis was performed to further maximize the reliability of the results.

Findings revealed that a proactive and systematic approach should be adopted and DCM practices should be initiated before any disruption event is triggered. Accordingly, the proposed framework recommends DCM practices to be initiated early in the contract development phase since compensation for the disruption might be recovered only to the extent that the contract permits. The contract-related risks were given top priority by the experts so that the results of the fuzzy AHP analysis also verified the significance of the contract development phase. Besides contract-related risks, risks related to insufficient site observation, ignorance of the project team, cognitive bias and conflict of interest were determined as the most significant DCM risks, needing an urgent and sophisticated risk response plan. Lastly, results suggested that “Site observation and record-keeping” is the most formidable phase since the phase's implementation on a continuous basis could create unforeseen organizational challenges such as mismanagement of project records, especially in the dynamic and turbulent environment of the construction projects.

Disruption – which is caused mostly by change – is inevitable in construction projects due to their sophisticated nature. DCM, therefore, becomes crucial to compensate losses of contractors and eliminate or diminish the prolonged dispute resolution process. Existing studies, however, do not provide a comprehensive theoretical basis for the DCM life cycle and DCM life cycle's potential risks so that DCM life cycle's promising benefits can hardly be materialized. Thus, developing a DCM life cycle and associating DCM life cycle with risk management, this study is highly believed to make a promising theoretical contribution to the DCM domain since this is one of the earliest attempts in the literature. Additionally, this research provides construction practitioners with an insight into the effective implementation of DCM practices in construction projects.

One of the most decisive objectives of human resource management (HRM), essential for business performance, is to attract, maintain and engage a qualified workforce. This study aims to identify and prioritize the antecedents of employer branding, which are considered extremely important by potential applicants when they choose to join a particular employer.

The authors have adopted a popular multicriteria decision-making technique fuzzy analytical hierarchy process, to prioritize the identified antecedents. The modified Delphi techniques with the 22 experts have been conducted to validate the identified antecedents. Structured questionnaires were discussed, and their reliability was assessed using the expert’s opinion.

Results of this study indicate that potential applicants consider career advancement opportunities as the most important enabler that persuades them to join a particular employer. Future employees are also motivated to join if they are offered attractive compensation packages, which are distinct from competitors. Furthermore, corporate social responsibility is evolving as an antecedent of employer branding as potential candidates are attracted to employers who are socially responsible.

Employer branding can serve as a strategic HRM technique for any business seeking to attract, recruit, retain and involve outstanding employees, as the success of the organization is determined by how its image is built, communicated and promoted. This study provides insights for HR managers and practitioners who can think of developing an effective employer brand communication that offers a distinct and in-imitable image and reputation as an employer of choice.

This study is unique, as it offers meaningful visions to HR practitioners and experts for designing employer branding strategies for attracting potential applicants to join their organizations.

Previous literature has identified human resources as a key source of competitive advantage in organizations of all sizes. However, Small and Medium-sized Enterprises (SMEs) face difficulty in comprehensively implementing all recommended Human Resource Management (HRM) functions. In this study, we shed light on the field of HRM in SMEs by focusing on the context of Greek Small and Medium-sized Hotels (SMHs), which represent a dominant private sector employer across the country.

Using a fuzzy-set qualitative comparative analysis (fsQCA) and 34 in-depth interviews with SMHs' owners/managers, we explore the HRM conditions leading to high levels of performance, while taking into consideration the influence of internal key determinants.

We uncover three alternative successful HRM strategies that maximize business performance, namely the Compensation-based performers, the HRM developers and the HRM investors. Each strategy fits discreet organizational characteristics related to company size, ownership type and organizational structure.

To the best of the authors' knowledge this is among the first empirical studies that examine different and equifinal performance-enhancing configurations of HRM practices in SMHs.

Omnidirectional mobile robots with a special type of wheel structure can realize flexible motion with all three degrees of freedom in a plane. But the driving method brings large disturbance, which affects motion accuracy and stability. This study aims to improve the motion control accuracy of the omnidirectional mobile platform with MY3 wheels (MY3-OMR), a new fuzzy active disturbance rejection control (FADRC) method with adaptivity is proposed.

Based on the basic mechanical structure and drive characteristics of MY3-OMR, the dynamics model of the system is established. The linear active disturbance rejection control (LADRC) system is designed to reduce the interference of nonlinear factors in this dynamics model. A fuzzy controller is introduced to realize the online adjustment of the parameters of the LADRC, which further improves the anti-disturbance performance of the system.

The control method proposed in this paper is compared and analyzed with other methods by simulation and experiment. Results show that the proposed method has better tracking and robustness, which effectively improves the control accuracy of trajectory tracking of MY3-OMR.

A FADRC method with adaptivity is proposed by combining fuzzy control and LADRC. The motion accuracy and anti-interference ability of the MY3-OMR are improved by this control method, which lays a foundation for the subsequent application of MY3-OMR.

Considering the unmeasurable states of the systems and the previewed reference signal, a novel fuzzy observer-based preview controller, which is a mixed controller of the fuzzy observer-based controller, fuzzy integrator and preview controller, is considered to address the tracking control problem.

The authors employ an augmentation technique to construct an augmented error system for uncertain T-S fuzzy discrete-time systems with time-varying uncertainties. Additionally, the authors obtain the corresponding linear matrix inequality (LMI) conditions for designing the preview controller.

This paper discusses the preview tracking problem for nonlinear systems. First, considering the unmeasurable states of the systems and the previewed reference signal, a novel fuzzy observer-based preview controller, which is a mixed controller of the fuzzy observer-based controller, fuzzy integrator, and preview controller, is considered to address the tracking control problem. Then, using the fuzzy Lyapunov functional with the linear matrix inequality (LMI) technique, new sufficient conditions for the asymptotic stability of the augmented system are derived by applying the LMI technique. The preview controller and fuzzy observer can be designed in one step. Finally, a numerical example is used to illustrate the effectiveness of the results.

An augmented error system is successfully constructed by the state augmentation approach. A novel preview controller is designed to address the tracking control problem. The preview controller and fuzzy observer can be designed in one step.

To improve the position tracking efficiency of the upper-limb rehabilitation robot for stroke hemiplegia patients, the optimization Learning rate of the membership function based on the fuzzy impedance controller of the rehabilitation robot is propose.

First, the impaired limb’s damping and stiffness parameters for evaluating its physical recovery condition are online estimated by using weighted least squares method based on recursive algorithm. Second, the fuzzy impedance control with the rule has been designed with the optimal impedance parameters. Finally, the membership function learning rate online optimization strategy based on Takagi-Sugeno (TS) fuzzy impedance model was proposed to improve the position tracking speed of fuzzy impedance control.

This method provides a solution for improving the membership function learning rate of the fuzzy impedance controller of the upper limb rehabilitation robot. Compared with traditional TS fuzzy impedance controller in position control, the improved TS fuzzy impedance controller has reduced the overshoot stability time by 0.025 s, and the position error caused by simulating the thrust interference of the impaired limb has been reduced by 8.4%. This fact is verified by simulation and test.

The TS fuzzy impedance controller based on membership function online optimization learning strategy can effectively optimize control parameters and improve the position tracking speed of upper limb rehabilitation robots. This controller improves the auxiliary rehabilitation efficiency of the upper limb rehabilitation robot and ensures the stability of auxiliary rehabilitation training.