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The purpose of this paper is to show the relevance attributed to sustainability management control tools (SMCTs) and their real use. Mainly, this study aims to shed light on the approaches, motivations and difficulties encountered in SMCTs adoption by the most sustainable Italian companies, as well as their effectiveness.

Using a pre-structured qualitative survey method, the authors grasped information about external and internal dimensions of sustainability management in light of institutional and resource-based view theories. Data are elaborated with two methods: a regime analysis to assess the relevance of SMCTs and a descriptive analysis to investigate the “aim”, “which” and “how” of the SMCTs' use by companies listed in sustainability indices.

Informal SMCTs prevailed over formal ones. There is a discrepancy between attention paid to some tools praised in the literature and their knowledge and use. In addition, a significant gap exists between what is desired and what is achieved in terms of effectiveness. Further, although sustainability management is primarily oriented towards the external perspective, SMCTs can be key to improving both the disclosure and management of sustainability.

The criteria for the selection of the sample resulted in a small number of analysed companies, which allowed us to gain insight into what happens inside the listed Italian companies in the most important sustainability indices. These companies have sustainability-oriented management, which also probably safeguards their advantage linked to inclusion in these indices.

This paper provides food for thought for companies engaged in non-financial disclosure and for those who aim to implement SMCTs. It shows the need to reinforce formal sustainability control tools, also through dissemination of major knowledge about the implementation of these tools, and to encourage sponsorship from top levels of management.

Compared with SMCT research using a theoretical or case study approach, this study uniquely undertakes extensive research on the perceived effectiveness of SMCTs in achieving sustainability goals and the difficulties in implementing them, thereby highlighting a discrepancy between some tools emphasised in the literature and those infrequently used in sustainability-oriented companies.

This paper aims to provide a mathematical modeling and design of H-infinity controller for an autonomous vertical take-off and landing (VTOL) Quad Tiltrotor hybrid unmanned aerial vehicles (UAVs). The variation in the aerodynamics and model dynamics of these aerial vehicles due to its tilting rotors are the key issues and challenges, which attracts the attention of many researchers. They carry parametric uncertainties (such as non-linear friction force, backlash, etc.), which drives the designed controller based on the nominal model to instability or performance degradation. The controller needs to take these factors into consideration and still give good stability and performance. Hence, a robust H-infinity controller is proposed that can handle these uncertainties.

A unique VTOL Quad Tiltrotor hybrid UAV, which operates in three flight modes, is mathematically modeled using Newton–Euler equations of motion. The contribution of the model is its ability to combine high-speed level flight, VTOL and transition between these two phases. The transition involves the tilting of the proprotors from 90° to 0° and vice-versa in 15° intervals. A robust H-infinity control strategy is proposed, evaluated and analyzed through simulation to control the flight dynamics for different modes of operation.

The main contribution of this research is the mathematical modeling of three flight modes (vertical takeoff–forward, transition–cruise-back, transition-vertical landing) of operation by controlling the revolutions per minute and tilt angles, which are independent of each other. An autonomous flight control system using a robust H-infinity controller to stabilize the mode of transition is designed for the Quad Tiltrotor UAV in the presence of uncertainties, noise and disturbances using MATLAB/SIMULINK. This paper focused on improving the disturbance rejection properties of the proposed UAV by designing a robust H-infinity controller for position and orientation trajectory regulation in the presence of uncertainty. The simulation results show that the Tiltrotor achieves transition successfully with disturbances, noise and uncertainties being present.

A novel VTOL Quad Tiltrotor UAV mathematical model is developed with a special tilting rotor mechanism, which combines both aircraft and helicopter flight modes with the transition taking place in between phases using robust H-infinity controller for attitude, altitude and trajectory regulation in the presence of uncertainty.

The purpose of this paper is to resolve the problem of the dynamic response performance of the driving control system for a six-wheeled planetary rover. An adaptive sliding mode controller based on an improved genetic algorithm (IGA) to tune PID sliding surface parameters was used in the driving control system of the planetary rover.

First, the mathematical model of planetary rover driving control is established. Second, according to sliding mode variable structure control, an equivalent controller and a disturbance controller are constructed to solve the problem of a multi-disturbance nonlinear driving control system of planetary rovers and an IGA is used to tune PID parameters.

Simulation results show that the proposed control algorithm improves the accuracy of the driving control system and optimizes the smoothness of rover motion control.

The controller based on the IGA to tune PID sliding surface parameters has good self-adaptability and real-time controllability for the control object which is difficult to present a precise mathematical model.

The advanced control method is adopted to solve the uncertainty and external interference of planetary rovers in a complex environment. The mathematical model of the six-wheeled rover is established as the control object and the uncertainty and external disturbance of the model are considered. The controller based on IGA has good adaptability and real-time performance and the control algorithm can be used to drive robots in complex environments.

This paper aims to propose output feedback-based control algorithms for the flight control system of a scaled, un-crewed helicopter in its hover flight mode.

The proposed control schemes are based on H_∞ control and composite nonlinear control. The gains of the output feedback controllers are obtained as the solution of a set of linear matrix inequalities (LMIs).

In the proposed schemes, the finite-time convergence of system states to trim condition is achieved with minimum deviation from the steady-state. As the proposed composite nonlinear output feedback design improves the transient response, it is well suited for a scaled helicopter flight. The use of measured output vector instead of the state vector or its estimate for feedback provides a simple control structure and eliminates the need for an observer in real-time application. The proposed control strategies are relevant to situations in which a simple controller is essential due to economic factors, reliability and hardware implementation constraints.

The proposed control strategies are relevant to situations in which a simple controller is essential due to economic factors, reliability and hardware implementation constraints. They also have significance in applications where the number of measurement quantities needs to be minimized such as in a fully functional rotor-craft unmanned aerial vehicle.

The developed output feedback control algorithms can be used in small-scale helicopters for numerous civilian and military applications.

This work addresses the LMI-based formulation and solution of an output feedback controller for a hovering un-crewed helicopter. The stability and robustness of the closed-loop system are proved mathematically and the performance of the proposed schemes is compared with an existing strategy via simulation studies.

An alignment between financial and operational measures is an essential element to capture the lean productivity improvements enabling supply chain sustainability. With the aim of supporting small and medium-sized enterprises (SMEs) in addressing corporate sustainability challenges, this study aims to examine the impact of leanness on supply chain sustainability, and the moderating role of sustainability control systems (SCS) on the relationship between leanness and supply chain sustainability.

Drawing on lean manufacturing and the levers of control framework, survey data was collected from 106 manufacturing SMEs in Sri Lanka. Moderated multiple regression analysis was used to test the proposed hypotheses.

The study finds that lean manufacturing practices, such as just-in-time deliveries, quality management, environmental management and employee involvement show a significant positive impact on supply chain sustainability. As proposed, the interactive use of SCS shows a significant, positive moderating impact on the relationship between employee involvement and social supply chain sustainability. The diagnostic use of SCS negatively moderates the relationships between just-in-time deliveries and economic supply chain sustainability, and environmental management and economic supply chain sustainability. However, both interactive and diagnostic uses of SCS do not show any significant moderating impact between lean manufacturing and environmental supply chain sustainability.

The following limitations should be taken into account in interpreting the results and implications of this study. Firstly, the study refers to supply chain sustainability as environmental, social and economic sustainability. As these concepts represent broader perspectives of sustainability, and no consensus on how to measure has yet been agreed, future studies may focus on other variables that might capture different perspectives of supply chain sustainability. Secondy, future researchers may further extend the role of SCS (including all four control systems – belief, boundary, interactive and diagnostic) in examining the impact of leanness on supply chain sustainability. Thirdly, this study has considered a sample of manufacturing SMEs in the Western province in Sri Lanka. The results should be carefully generalised to other manufacturing organisations in Sri Lanka and beyond. Finally, future studies may also investigate the impact of leanness on supply chain sustainability by using alternative methodologies, such as multiple case studies.

SMEs are more likely to focus on diagnostic control systems with the aim of promoting economic supply chain sustainability. However, the findings reveal that manufacturing SMEs in the developing country context lack strong SCS to enable supply chain sustainability.

The authors examine the association between internal control quality (ICQ) and voluntary disclosure and test whether chief executive officer (CEO) duality, as a proxy for CEO structural power, moderates such a relationship in an emerging market (Egypt).

ICQ is measured using a survey of external auditors, while a content analysis approach is used to measure the level of voluntary disclosure in annual reports.

Based on a sample of 512 firm-year observations over the period of 2007–2014, the authors document that ICQ is positively and significantly associated with voluntary disclosure, suggesting that better controls improve corporate reporting policy. In addition, CEO duality moderates the association between ICQ and voluntary disclosure since this positive relationship association becomes insignificant for companies characterised by CEO duality. These results remain stable after controlling for endogeneity (self-selection problem), political instability and industry characteristics.

The findings of the study provide preliminary evidence on the association between ICQ and voluntary disclosure, and how CEO structural power may affect this association. Future empirical investigations may extend this work to cover the relationship between ICQ and other attributes of corporate transparency including earnings quality and accounting conservatism.

The findings highlight the need for Egyptian regulators to enact new rules obliging firms to communicate information about ICQ or charging auditors to report information about firm's ICQ in their reports. The results also alert policymakers about the adverse effect of combined leadership structure (CEO duality) since it mitigates the positive impact of ICQ on voluntary disclosure.

The authors contribute to internal control literature by exploring the association between ICQ and voluntary disclosure on an emergent unregulated market with respect to internal control disclosure. They also highlight how CEO duality, as a proxy for CEO power, mitigates the beneficial effect of ICQ on corporate reporting policy on the Egyptian stock exchange (EGX).

Modeling and control of bead geometry in wire and arc additive manufacturing is significant as it affects the whole manufacturing process. The purpose of this paper is to establish an efficient model to control the bead geometry with fewer experiments in wire and arc additive manufacturing (WAAM).

A multi-sensor system is established to monitor the process parameters and measure the bead geometry information. A dynamic parameters experimental method is proposed for rapid modeling without dozens of experiments. A deep learning method is used for bead modeling and control. To adaptively control the bead geometry in real-time, a closed-loop control system was developed based on the bead model and in situ monitoring.

A series of experiments were conducted to train, test and verify the feasibility of the method and system, and the results showed that the proposed method can build the bead model rapidly with high precision, and the closed-loop system can control the forming geometry adaptively.

The proposed modeling method is novel as the experiment number is reduced. The dynamic parameters experimental method is effective with high precision. The closed-loop control system can control the bead geometry in real-time. The forming accuracy is elevated.

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.

To improve the robustness of missile control system and reduce the error, a missile attitude adaptive control method based on active disturbance rejection control technology (ADRC) and BP neural network is innovatively proposed.

ADRC improves the performance of the missile control system by estimating and eliminating the total disturbance of the system. BP neural network adjusts the parameters of ADRC controller according to the state of the system to realize adaptive control. Based on the control system and missile dynamics model, the convergence analysis of the extended state observer and the stability analysis of the closed-loop system after embedding BP neural network are given.

The simulation results show that the adaptive control method can adjust the coefficient of error feedback rate according to the system input, output and error change rate, which accelerates the response speed of missile attitude angle and reduces the attitude angle error.

BP–ADRC further improves the robustness and environmental adaptability of the missile control system. The BP–ADRC control method proposed in this paper is proved feasible.

Different from the traditional ADRC, the BP–ADRC feedback signal proposed in this paper uses the output signal and its rate of the closed-loop system instead of the system state quantity estimated by extended state observer (ESO). This innovative method combined with BP neural network can make the system output meet the requirements when ESO has errors in the estimation of missile dynamics model.