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The purpose of this paper is to investigate the effect of complete versus partial observations of service failure and recovery. This study also aims at investigating the effect of observing customers’ need for cognitive closure and types of compensation that a service provider offers.

Two experiments are conducted to test the research hypotheses. The authors use scenarios describing failure and recovery encounters that occur to a target customer at restaurant settings, and through manipulation of complete versus partial observations, they investigate observers’ attitudes and behavioral intentions.

The results suggest that customers with a partial observation are less forgiving than those with a complete observation. In particular, the former sympathized more with a target customer, blamed a service provider more and a target customer less and had lower repurchase intentions than the latter. The authors find that the need for cognitive closure heightens this tendency following a partial observation of service failure. They also find that following a complete (versus partial) observation, observers reacted more favorably to service recovery when it included (versus did not include) monetary compensation.

This research studies the effect of locus of causality following a partial versus complete observation. Future research could further examine the effect of stability and controllability. Also, the authors examined the effect of the need for cognitive closure on evaluations of service failure following a partial versus complete observation. Future research could examine the effect of some other individual difference variables.

The results offer some measures to be taken by practitioners. In particular, practitioners are advised to not offer monetary compensation when majority of observers have had a partial observation. Moreover, they are advised to offer some explanation in a timely and effective manner to ensure observers who are under the negative impact of a partial observation have some information so that they revisit their service evaluations.

The literature assumes that in failure and recovery incidents, all observing customers would know the entire story. This research challenges this assumption and highlights the key role of observation type (partial versus complete observation). Further, this research examines the effect of the need for cognitive closure on service evaluations following a partial versus complete observation. The current research finds that supposedly favorable measures by a firm (i.e. monetary compensation) may in fact backfire when a partial observation is at play.

Many companies in industry concentrate a lot of energy on drawing up training programmes which tackle the difficult problem of making workers conscious of the dangers confronting them in their place of work. Many programmes include aspects of accident prevention dramatically illustrated by “what happens when …” situations, appeals to safety observers to drive home to fellow‐workers the necessity of wearing goggles, ear plugs, safety shoes etc. In other words, the primary task of the safety observer is to observe skilfully and prevent unsafe acts which could endanger health and safety at work. How often, however, is the safety observer himself fully aware of the role which he has accepted? How beneficial can role‐awareness be in carrying out safety training measures at shop‐floor level? Finding an answer to this question was, for us, the basic part of a new approach to safety training which was to be tested with a group of safety observers in one of our production plants.

To meet the need of reducing the cost of industrial systems, sensorless control applications on electrical machines are increasing day by day. This paper aims to improve the performance of the sensorless induction motor control system. To do this, the speed observer is designed based on the combination of the sliding mode and the fractional order integral.

Super-twisting sliding mode (STSM) and Grünwald–Letnikov approach are used on the proposed observer. The stability of the proposed observer is verified by using Lyapunov method. Then, the observer coefficients are optimized for minimizing the steady-state error and chattering amplitude. The optimum coefficients (c₁, c₂, k_i and λ) are obtained by using response surface method. To verify the effectiveness of proposed observer, a large number of experiments are performed for different operation conditions, such as different speeds (500, 1,000 and 1,500 rpm) and loads (100 and 50 per cent loads). Parameter uncertainties (rotor inertia J and friction factor F) are tested to prove the robustness of the proposed method. All these operation conditions are applied for both proportional integral (PI) and fractional order STSM (FOSTSM) observers and their performances are compared.

The observer model is tested with optimum coefficients to validate the proposed observer effectiveness. At the beginning, the motor is started without load. When it reaches reference speed, the motor is loaded. Estimated speed and actual speed trends are compared. The results are presented in tables and figures. As a result, the FOSTSM observer has less steady-state error than the PI observer for all operation conditions. However, chattering amplitudes are lower in some operation conditions. In addition, the proposed observer shows more robustness against the parameter changes than the PI observer.

The proposed FOSTSM observer can be applied easily for industrial variable speed drive systems which are using induction motor to improve the performance and stability.

The robustness of the STSM and the memory-intensive structure of the fractional order integral are combined to form a robust and flexible observer. This paper grants the lower steady-state error and chattering amplitude for sensorless speed control of the induction motor in different speed and load operation conditions. In addition, the proposed observer shows high robustness against the parameter uncertainties.

The purpose of this paper is to present an actuator fault detection method for unmanned aerial vehicles (UAVs) based on interval observer and extended state observer.

The proposed algorithm has very little model dependency. Therefore, a six-degree-of-freedom linear equation of UAVs is first established, and then, combined with actuator failure and external disturbances in flight control, a steering gear model with actuator failure (such as stuck bias and invalidation) is designed. Meanwhile, an extended state observer is designed for fault detection. Moreover, a fault detection scheme based on interval observer is designed by combining fault and disturbances.

The method is testified on the extended state observer and the interval observer under the failure of the steering gear and bounded disturbances. The simulation results show that the two types of fault detection schemes designed can successfully detect various types of faults and have high sensitivity.

This research paper studies the failure detection scheme of the UAVs’ actuator. The fault detection scheme in this paper has better performance on actuator faults and bounded disturbances than using regular fault detection schemes.

The purpose of this paper is to design linear quadratic regulator (LQR) based Luenberger observer for the estimation of unknown states of aircraft.

In this paper, the LQR-based Luenberger observer is deliberated for autonomous level flight of unmanned aerial vehicle (UAV) which has been attained productively. Various modes like phugoid and roll modes are exploited for controlling the rates of UAV. The Luenberger observer is exploited for estimation of the mysterious states of the system. The rates of roll, yaw and pitch are used as an input to the observer, while the remaining states such as velocities and angles have been anticipated. The main advantage of using Luenberger observer was to reduce the cost of the system which has been achieved lucratively. The Luenberger observer proposes sturdiness at the rate of completion to conquest over the turmoil and insecurities to overcome the privileged recital. The FlightGear simulator is exploited for the endorsement of the recital of the Luenberger observer-based autopilot. The level flight has been subjugated lucratively and has been legitimated by exploiting the FlightGear simulator. The authenticated and the validated results are offered in this paper. Microsoft Visual Studio has been engaged as a medium between the MATLAB and FlightGear Simulator.

The suggested observer based on LQR ensures the lucrative approximation of the unknown states of the system as well as the successful level flight of the system. The Luenberger observer is used for approximation of states while LQR is used as controller.

In this research work, not only the estimation of unknown states of both longitudinal and lateral model is made but also the level flight is achieved by using those estimated states and the autopilot is validated by using the FlightGear, while in most of the research work only the estimation is made of only longitudinal or lateral model.

W. Ross Ashby’s elementary non-trivial machine, known in the cybernetic literature as the “Ashby Box,” has been described as the prototypical example of a black box system. As far as it can be ascertained from Ashby’s journal, the intended purpose of this device may have been to exemplify the environment where an “artificial brain” may operate. This paper describes the construction of an elementary observer/controller for the class of systems exemplified by the Ashby Box – variable structure black box systems with parallel input.

Starting from a formalization of the second-order assumptions implicit in the design of the Ashby Box, the observer/controller system is synthesized from the ground up, in a strictly system-theoretic setting, without recourse to disciplinary metaphors or current theories of learning and cognition, based mainly on guidance from Heinz von Foerster’s theory of self-organizing systems and W. Ross Ashby’s own insights into adaptive systems.

Achieving and maintaining control of the Ashby Box requires a non-trivial observer system able to use the results of its interactions with the non-trivial machine to autonomously construct, deconstruct and reconstruct its own function. The algorithm and the dynamical model of the Ashby Box observer developed in this paper define the basic specifications of a general purpose, unsupervised learning architecture able to accomplish this task.

The problem exemplified by the Ashby Box is fundamental and goes to the roots of cybernetic theory; second-order cybernetics offers an adequate foundation for the mathematical modeling of this problem.

The purpose of this paper is to investigate the effect of interdependent vs independent self-construal on service satisfaction, following the observation of failure and recovery experienced by a fellow customer.

Three experiments were conducted to test the research hypotheses.

After service failure, interdependent observers react less favorably compared to independent observers. After high recovery compensation, interdependent observers react more favorably compared to independent observers. The effects are driven by differences in perceived interactional and distributive justice.

This study uses three scenario-based experiments to test the hypotheses. While providing greater control of the experimental conditions, the external validity of the results is to some extent sacrificed. Moreover, this research does not investigate observers’ reactions to the interactional aspect of recovery.

When handling service failure, firms are required to anticipate and address not only the responses of the target customers involved but also those of potential observers. Providers can accordingly use available customer information to gauge customers’ likely self-construal and to adjust their service delivery and recovery tactics. Providers can influence observing customers’ reactions by creating a servicescape that activates a desired self-construal.

This research is one of a few to examine the effect of service failure and recovery on observing customers, and the first to do so via the lens of self-construal. It contributes to the literature on service failure and recovery and the literature on self-construal and has practical implications for service providers. The value of this research is further highlighted given the increasingly public nature of services and the multicultural context of service delivery.

Although supplier-initiated punishment is widely used to manage distributors’ opportunism, its spillover effect on unpunished distributors (i.e. observers) within the same distribution network remains under-researched. Specifically, this paper aims to investigate the curvilinear effect of punishment severity on an observer’s opportunism, and how such an effect is contingent on the observer’s network position.

This paper uses regression analysis with survey data gathered from 218 distributors in China’s automobile industry.

Punishment severity has an inverted U-shaped effect on the observers’ opportunism, and such effect is weakened by both the observers’ network centrality and their degree of dependence on the supplier.

The findings should encourage suppliers to focus more on the spillover effects of punishment on observers. To this end, the supplier must deliberately initiate the appropriate level of punishment severity against its distributors because an inappropriate level of punishment severity (e.g. too lenient) may unexpectedly raise the unpunished observers’ level of opportunism. Moreover, the supplier should be fully aware that observers’ specific network positions may produce varying spillover effects of the punishment.

This study enriches the literature on channel governance by revealing the curvilinear mechanism through which punishment severity influences observers’ opportunism. By applying social learning theory to channel punishment research, this study unveils both the inhibitive learning and the imitative learning forces inherent in a single punishment event, and it delineates their joint effect on an observer’s opportunism. In addition, this study outlines the observer’s vertical and horizontal relationships within the distribution network and explores their contingent roles in determining the spillover effects of punishment.

The purpose of this paper is to improve the performance of sensorless vector control of induction motor drives by developing a new sliding mode observer for rotor speed and fluxes estimation from measured stator currents and voltages and estimated stator currents.

In the present paper, the discontinuity in the sliding mode observer is smoothed inside a thin boundary layer using fuzzy logic techniques instead of sign function to reduce efficiently the chattering phenomenon that affects the rotor speed.

The feasibility of the proposed fuzzy sliding mode observer has been verified by experimentation. The experimental results are obtained with a 1 kW induction motor using a dSPACE system with DS1104 controller board showing clearly the effectiveness of the proposed approach in terms of dynamic performance compared to the classical sliding mode observer.

The experimental results of the whole control structure highlights that this kind of sensorless induction motor drive can be used for variable speed drive in industrial applications such as oil drilling, electric vehicles, high speed trains (HSTs) and conveyers. Such drives may work properly at zero and low speed in both directions of rotation.

Both the proposed speed observer and the classical sliding mode observer have been developed and implemented experimentally with other adaptive observers for detailed comparison under different operating conditions, such as parameter variation, no-load/load disturbances and speed variations in different speed operation regions.

Fault detection, isolation and reconfiguration of the flight control system is an important problem to obtain healthy flight. This paper aims to propose an integrated approach for aircraft fault-tolerant control.

The integrated structure includes a Kalman filter to obtain without noise, a full order observer for sensor fault detection, a GOS (generalized observer scheme) for sensor fault isolation and a fuzzy controller to reconfigure of the healthy sensor. This combination is simulated using the state space model of a lateral flight control system in case of disturbance and under sensor fault scenario.

Using a dedicated observer scheme, the detection and time of sensor fault are correct, but the sensor fault isolation is evaluated incorrectly while the faulty sensor is isolated correctly using GOS. The simulation results show that the suggested approach works affectively for sensor faults with disturbance.

This paper proposes an integrated approach for aircraft fault-tolerant control. Under this framework, three units are designed, one is Kalman filter for filtering and the other is GOS for sensor fault isolation and another is fuzzy logic for reconfiguration. An integrated approach is sensitive to faults that have disturbances. The simulation results show the proposed integrated approach can be used for any linear system.