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With the increasing demands of industrial applications, it is imperative for robots to accomplish good contact-interaction with dynamic environments. Hence, the purpose of this research is to propose an adaptive fractional-order admittance control scheme to realize a robot–environment contact with high accuracy, small overshoot and fast response.

Fractional calculus is introduced to reconstruct the classical admittance model in this control scheme, which can more accurately describe the complex physical relationship between position and force in the interaction process of the robot–environment. In this control scheme, the pre-PID controller and fuzzy controller are adopted to improve the system force tracking performance in highly dynamic unknown environments, and the fuzzy controller is used to improve the trajectory, transient and steady-state response by adjusting the pre-PID integration gain online. Furthermore, the stability and robustness of this control algorithm are theoretically and experimentally demonstrated.

The excellent force tracking performance of the proposed control algorithm is verified by constructing highly dynamic unstructured environments through simulations and experiments. In simulations and experiments, the proposed control algorithm shows satisfactory force tracking performance with the advantages of fast response speed, little overshoot and strong robustness.

The control scheme is practical and simple in the actual industrial and medical scenarios, which requires accurate force control by the robot.

A new fractional-order admittance controller is proposed and verified by experiments in this research, which achieves excellent force tracking performance in dynamic unknown environments.

Traffic signal control is one of the oldest application areas of fuzzy sets in transportation. In general, fuzzy control is found to be superior in complex problems with multi-objective decisions. In traffic signal control, several traffic flows compete for the same time and space, and different priorities are often set to different traffic flows or vehicle groups

The public transport priorities are a very important part of the effective traffic signal control. Normally, the public transport priorities are programmed by using special algorithms, which are tailor-made for each intersection. The experiences have proved that this kind of algorithms can be very effective if some compensation algorithms and the traffic-actuated control mode are used. We believe that using the fuzzified public transport priority algorithms, the measures of effectiveness of traffic signal control can be even better. In this paper, our fuzzy control algorithm of the public transport priorities will be presented.

While it is widely acknowledged that host governments play some role in framing the governance structure that is available to multinational corporations, some argue that in recent years the influence of host governments on MNCs in terms of the level of ownership and control over their foreign ventures has diminished. The authors examine the degree of MNC’s control in foreign investment by presenting and testing a model of government influences on MNC’s control over its foreign market venture. Based on a survey of U.S. MNCs, the authors find that host government preference does influence MNC’s ownership control over its foreign market venture, which in turn influences its management control over the venture.

The most basic solution for monitoring position and attitude of an UA is through direct line-of-sight. Because they are usually standing outside, a pilot that maintains direct line-of-sight with the aircraft is usually referred to as the EP, as opposed to an internal pilot (IP) who obtains position and attitude information electronically while inside of a ground control station (GCS). Flight using an EP represents the most basic solution to the problem of separating the pilot from the aircraft while still enabling the pilot to monitor the location and attitude of the aircraft. Pilot perspective is changed from an egocentric to an exocentric point of view. Maintaining visual contact with the UA, the EP can control the aircraft using a hand-held radio control box. Many of these control boxes are similar to those used by radio-controlled aircraft hobbyists and provide direct control of the flight surfaces of the aircraft through the use of joysticks on the box. Very little automation is involved in the use of such boxes, which control the flight surfaces of the aircraft.

Most of the 3D printing machines do not comply with the requirements of on-site, large-scale multi-story building construction. This paper aims to propose the conceptualization of a tower crane (TC)-based 3D printing controlled by artificial intelligence (AI) as the first step towards a large 3D printing development for multi-story buildings. It also aims to overcome the most important limitation of additive manufacturing in the construction industry (the build volume) by exploiting the most important machine used in the field: TCs. It assesses the technology feasibility by investigating the accuracy reached in the printing process.

The research is composed of three main steps: firstly, the TC-based 3D printing concept is defined by proposing an aero-pendulum extruder stabilized by propellers to control the trajectory during the extrusion process; secondly, an AI-based system is defined to control both the crane and the extruder toolpath by exploiting deep reinforcement learning (DRL) control approach; thirdly the proposed framework is validated by simulating the dynamical system and analysing its performance.

The TC-based 3D printer can be effectively used for additive manufacturing in the construction industry. Both the TC and its extruder can be properly controlled by an AI-based control system. The paper shows the effectiveness of the aero-pendulum extruder controlled by AI demonstrated by simulations and validation. The AI-based control system allows for reaching an acceptable tolerance with respect to the ideal trajectory compared with the system tolerance without stabilization.

In related literature, scientific investigations concerning the use of crane systems for 3D printing and AI-based systems for control are completely missing. To the best of the authors’ knowledge, the proposed research demonstrates for the first time the effectiveness of this technology conceptualized and controlled with an intelligent DRL agent.

The results provide the first step towards the development of a new additive manufacturing system for multi-storey constructions exploiting the TC-based 3D printing. The demonstration of the conceptualization feasibility and the control system opens up new possibilities to activate experimental research for companies and research centres.

The purpose of this inductive, exploratory study is to provide foundational insights into the role of management control in dealing with dysfunctional behaviour within accounting schools in changing environment of Australian universities.

Evidence is drawn from semi-structured interviews with 28 current or previous heads of school, research deans, deans of teaching and learning, school managers and human resource managers from 16 Australian universities and interpreted from the theoretical perspective of rational choice theory.

The findings suggest the incidence of a range of dysfunctional behaviours occurring in accounting schools. Even when such behaviours are limited in frequency, their consequences are nevertheless found to have far-ranging and potentially destructive change impacts for both individuals and the university. Formal management control systems designed to address such behaviours are perceived to be largely ineffective in identifying, managing, eliminating or even mitigating the consequences of such dysfunctionality. Instead, it is informal control processes that are preferred in dealing with dysfunctionality.

This study enhances our understanding of the role of management control in dealing with dysfunctional behaviour within university accounting schools, and points not only to the difference between the design and use of management controls but also to the implications of this disconnect between the underlying intent of control design and their actual use in the context of environments that are subject to significant change.

The purpose of this paper is to present an economic–statistical design (ESD) for the Bayesian X‾ control chart based on predictive distribution with two types of informative and noninformative prior distributions.

The design used in this study is based on determining the control chart of the predictive distribution and then its ESD. The new proposed cost model is presented by considering the conjugate and Jeffrey's prior distribution in calculating the expected total cycle time and expected cost per cycle, and finally, the optimal design parameters and related costs are compared with the fixed ratio sampling (FRS) mode.

Numerical results show decreases in costs in this Bayesian approach with both Jeffrey's and conjugate prior distribution compared to the FRS mode. This result shows that the Bayesian approach which is based on predictive density works better than the classical approach. Also, for the Bayesian approach, however, there is no significant difference between the results of using Jeffrey's and conjugate prior distributions. Using sensitivity analysis, the effect of cost parameters and shock model parameters and deviation from the mean on the optimal values of design parameters and related costs have been investigated and discussed.

This research adds to the body of knowledge related to quality control of process monitoring systems. This paper may be of particular interest to quality system practitioners for whom the effect of the prior distribution of parameters on the quality characteristic distribution is important.

economic statistical design (ESD) of Bayesian control charts based on predictive distribution is presented for the first time.

This study examines the relationship between the use of management controls and the perception of meaningful work. Meaningful work is an important driver of individual performance of managers, and employees and can be enabled by sufficient use of management controls. The purpose of this paper is to address this issue.

Based on bibliometric analyses and a structured literature review of academic research studies from the organizational, management and accounting literature, the authors develop a conceptual model of the relationship between the use of management controls and the perception of meaningful work.

First, the authors propose that the use of formal management controls in a system (i.e. the levers of the control framework) is more powerful than using unrelated formal controls only. Second, they suggest that the interaction of a formal control system together with informal controls working as a control package can even stretch the perception of meaningful work. Third, they argue that the intensity of the control use matters to enhance the perception of meaningful work (inverted u-shaped relationship).

This study presents the first conceptual model of the relationship between the use of management controls and the perception of meaningful work. It provides valuable implications for practice and future research in the field of performance management.

Because steadily growing consumption is not beneficial for nature and climate and is not the same as increasing well-being, an anti-consumerism movement has formed worldwide. The renouncement of dispensable consumption will, however, only establish itself as a significant lifestyle if consumers do not perceive reduced consumption as a personal sacrifice. Since prior research has not yielded a consistent understanding of the relationship between anti-consumption and personal well-being, this paper aims to examine three factors about which theory implies that they may moderate this relationship: decision-control empowerment, market-control empowerment and the value of materialism.

The analysis is based on data from a large-scale, representative online survey (N = 1,398). Structural equation modelling with latent interaction effects is used to test how three moderators (decision-control empowerment, market-control empowerment and materialism) affect the relationship amongst four types of anti-consumption (e.g. voluntary simplicity) and three different well-being states (e.g. subjective well-being).

While both dimensions of empowerment almost always directly promote consumer well-being, significant moderation effects are present in only a few but meaningful cases. Although the materialism value tends to reduce consumers’ well-being, it improves the well-being effect of two anti-consumption styles.

Using only one sample from a wealthy country is a limitation of the study. Researchers should replicate the findings in different nations and cultures.

Consumer affairs practitioners and commercial marketing for sustainably produced, high-quality and long-lasting goods can benefit greatly from these findings.

This paper shows that sustainable marketing campaigns can more easily motivate consumers to voluntarily reduce their consumption for the benefit of society and the environment if a high level of market-control empowerment can be communicated to them.

This study provides differentiated new insights into the roles of consumer empowerment, i.e. both decision-control empowerment and market-control empowerment, and the value of materialism to frame specific relationships between different anti-consumption types and various well-being states.