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This study aims to assess how undergraduates’ exposure to entrepreneurship education (EE) may increase their volitional desire and behavioral control to start-up a business.

The model establishes three different paths from EE to entrepreneurial intention (EI): attraction and passion through desire and confidence through control. These paths are assessed by partial least-squares structural equation modeling in a sample of 650 undergraduates from Poland, Turkey and Portugal.

The most effective way by which EE may increase EI is by promoting a favorable change in the attractiveness of the entrepreneurship career. Contrary to expectations based on the literature, the effects of EE on perceived behavioral control are weak and limited to aspects related to financial control.

EE programs should consider desire and control in different phases of training, with the following learning outcomes: explore prospective rewards of an attractive entrepreneurial career, develop self-efficacy regarding management competences and gain control by assuring skills to cope with failure.

To the best of the authors’ knowledge, this study is the first to establish a path from EE to EI through passion and desire. It is also the first to consider entrepreneurial passion as a positive anticipated emotion in the model of goal-directed behavior. The results allow to relate the different paths with different learning outcomes of EE programs.

This paper aims to present a unified motion control scheme for quadcopters which not only solves the point stabilization and trajectory tracking problems but also the path following problem.

The control problem is solved based on the kinematic model of the unmanned aerial vehicles (UAV). Next, a dynamic compensation controller is considered through of a quadcopter-inner-loop system to independently track four velocity commands: forward, lateral, up/downward and heading rate. Stability and robustness of the whole control system are proved through the Lyapunov’s method. To evaluate the controller’s performance, a multi-user application which allows bilateral communication between a ground station and the Phantom 3 PRO quadrotor is developed.

The performance of the proposed unified controller is shown through real experiments for the different motion control objectives: point stabilization, trajectory tracking and path following. The experiments confirm the capability of the unified controller to solve different motion problems by an adequate selection of the control references.

This work proposes the design of three types of motion controllers, which can be switched to comply a task in outdoor. Based on the software development kit provided by the company DJI, an application to get and send data to the UAV is developed. By means of this application, the three tasks are tested and the robustness of the controllers is proved.

This paper aims to test the model of goal-directed behavior (MGB) in the prediction of entrepreneurial intentions of high school students. It also uncovers heterogeneity and differences in structural paths. The study aims to expand the toolbox of theoretical models that are useful to interpret entrepreneurial intentions by including the MGB. The MGB explains the role of desires, anticipated emotions and frequency of past behavior (FPB). These aspects are underplayed in other models.

The paper opted for a study using PLS path modeling. The authors applied questionnaires to 643 students (260 boys and 383 girls) from 34 high school institutions of a large metropolitan city in a developing country. Data analysis used a multi-group analysis and a finite mixture (FIMIX) approach.

The paper provides empirical insights about the antecedents of entrepreneurial intentions and confirms the role that desires and FPB have in their development. MGA results suggest that PBC relevance depends on gender, and emotions vary with socio economic level (SEL).

Research results are limited to high school students. Therefore, researchers are encouraged to test the proposed propositions further with university students and the general population in other developing and developed countries.

The paper includes implications for teaching curriculum and government policy in entrepreneurship. The results encourage the study of entrepreneurship from a young age and the importance of teaching how to overcome negative emotions in the entrepreneurial process.

This paper satisfies a recognized need to evaluate competing models that explain entrepreneurial intentions. The grouping analysis uncovers opportunities to develop innovative education and training strategies.

The main purpose of this paper is to understand the impact on the United Arab Emirates (UAE) economy of the objective of reducing its dependence on oil, trying to achieve the Gulf Cooperation Council (GCC) fiscal convergence criterion and the inevitable depletion of oil resources.

An 18 equation compact macro‐econometric model is constructed and is evaluated and calibrated employing dynamic simulation techniques. Optimal control techniques are used to analyze the economic impact of the three objectives listed above.

Each of the optimal control experiments that has been carried out has served to reinforce the fact that the UAE is still critically dependent on oil. An increase in the share of the non‐oil sector, adhering to the GCC fiscal criterion and any reduction in oil output production will affect government finances adversely.

The macro‐econometric model developed is for the UAE and further research is needed to see if the conclusions can be generalized to the other oil exporting countries.

The estimated macro‐econometric model and the optimal control experiments indicate to the policy makers the need to continue the diversification of the economy and for government to actively explore and enhance non‐hydrocarbon sources of revenue.

This paper develops a compact macro‐econometric model of the UAE and uses optimal control techniques which go well beyond the standard simulation techniques and the routine counter‐factual experiments to understand the working of the economy.

This paper aims to propose a new technique for programming robotized machining tasks based on intuitive human–machine interaction. This will enable operators to create robot programs for small-batch production in a fast and easy way, reducing the required time to accomplish the programming tasks.

This technique makes use of online walk-through path guidance using an external force/torque sensor, and simple and intuitive visual programming, by a demonstration method and symbolic task-level programming.

Thanks to this technique, the operator can easily program robots without learning every robot-specific language and can design new tasks for industrial robots based on manual guidance.

The main contribution of the paper is a new procedure to program machining tasks based on manual guidance (walk-through teaching method) and user-friendly visual programming. Up to now, the acquisition of paths and the task programming were done in separate steps and in separate machines. The authors propose a procedure for using a tablet as the only user interface to acquire paths and to make a program to use this path for machining tasks.

This paper aims to increase the safety of the robots’ operation by developing a novel method for real-time implementation of velocity scaling and obstacle avoidance as the two widely accepted safety increasing concepts.

A fuzzy version of dynamic movement primitive (DMP) framework is proposed as a real-time trajectory generator with imbedded velocity scaling capability. Time constant of the DMP system is determined by a fuzzy system which makes decisions based on the distance from obstacle to the robot’s workspace and its velocity projection toward the workspace. Moreover, a combination of the DMP framework with a human-like steering mechanism and a novel configuration of virtual impedances is proposed for real-time obstacle avoidance.

The results confirm the effectiveness of the proposed method in real-time implementation of the velocity scaling and obstacle avoidance concepts in different cases of single and multiple stationary obstacles as well as moving obstacles.

As the provided experiments indicate, the proposed method can effectively increase the real-time safety of the robots’ operations. This is achieved by developing a simple method with low computational loads.

This paper proposes a novel method for real-time implementation of velocity scaling and obstacle avoidance concepts. This method eliminates the need for modification of original DMP formulation. The velocity scaling concept is implemented by using a fuzzy system to adjust the DMP’s time constant. Furthermore, the novel impedance configuration makes it possible to obtain a non-oscillatory convergence to the desired path, in all degrees of freedom.

This paper aims to propose a new autonomous driving controller to calibrate the absolute heading adaptively. Besides, the second purpose of this paper is to propose a new angle-track loop with a mass regulator to improve the adaptability of the autonomous driving system under different loads and road conditions.

In this paper, the error model of heading is built and a new autonomous driving controller with heading adaptive calibration is designed. The new controller calculates the average lateral error by the self-adjusting interval window and calibrates the absolute heading through the incremental proportional–integral–derivative (PID) controller. A window-size adjustment strategy, based on the current lateral error and the derivative of lateral error, is proposed to improve both the transient and the steady-state responses. An angle-tracking loop with mass regulator is proposed to improve the adaptability of autonomous steering system under different loads and road conditions.

The experiment results demonstrate that this method can compensate the heading installation error and restrain the off-track error from 13.8 to 1.30 cm. The standard error of new controller is smaller than fuzzy-PID calibration controller and the accuracy of autonomous driving system is improved.

The accuracy of heading calibrated by the new controller is not affected by external factors and the efficiency of calibration is improved. As the model parameters of steering system can be obtained manually, the new autonomous steering controller has more simple structure and is easy to implement. Mass regulator is adjusted according to the road conditions and the mass of harvester, which can improve the system adaptability.

A major challenge for mission planning of aircraft is to generate flight paths in highly dynamic environments. This paper presents a new approach for online flight path planning with flight time constraints for fixed-wing UAVs. The flight paths must take into account the kinematic restrictions of the vehicle and be collision-free with terrain, obstacles and no-fly areas. Moreover, the flight paths are subject to time constraints such as predetermined time of arrival at the target or arrival within a specified time interval.

The proposed flight path planning algorithm is an evolution of the well-known RRT* algorithm. It uses three-dimensional Dubins paths to reflect the flight capabilities of the air vehicle. Requirements for the flight time are realized by skillfully concatenating two rapidly exploring random trees rooted in the start and target point, respectively.

The approach allows to consider static obstacles, obstacles which might pop up unexpectedly, as well as moving obstacles. Targets might be static or moving with constantly changing course. Even a change of the target during flight, a change of the target approach direction or a change of the requested time of arrival is included.

The capability of the flight path algorithm is demonstrated by simulation results. Response times of fractions of a second qualify the algorithm for real-time applications in highly dynamic scenarios.

The purpose of the paper is to design a nonlinear dynamic inversion (NDI) based robust fault-tolerant control (FTC) for aircraft longitudinal dynamics subject to system nonlinearities, aerodynamic parametric variations, external wind disturbances and fault/failure in actuator.

An uncertainty and disturbance estimator (UDE) technique is used to provide estimate of total disturbance enabling its rejection and thereby achieving robustness to the proposed NDI controller. As needed in the NDI design, the successive derivatives of the output are obtained through an UDE robustified observer making the design implementable. Further, a control allocation scheme consigns control command from primary actuator to the secondary one in the event of fault/failure in the primary actuator.

The robustness is achieved against the perturbations mentioned above in the presence of actuator fault/failure.

Lyapunov analysis proves practical stability of the controller–observer structure. The efficacy and superiority of the proposed design has been demonstrated through Monte-Carlo simulation.

Unlike in many FTC designs, robustness is provided against system nonlinearities, aerodynamic parametric variations, external wind disturbances and sinusoidal input disturbance using a single control law which caters for fault-free, as well as faulty actuator scenario.

This paper focuses on the application of a robotic technique for modeling a three-wheeled mobile robot (WMR), considering it as a multibody polyarticulated system. Then the dynamic behavior of the developed model is verified using a physical model obtained by Simscape Multibody.

Firstly, a geometric model is developed using the modified Denavit–Hartenberg method. Then the dynamic model is derived using the algorithm of Newton–Euler. The developed model is performed for a three-wheeled differentially driven robot, which incorporates the slippage of wheels by including the Kiencke tire model to take into account the interaction of wheels with the ground. For the physical model, the mobile robot is designed using Solidworks. Then it is exported to Matlab using Simscape Multibody. The control of the WMR for both models is realized using Matlab/Simulink and aims to ensure efficient tracking of the desired trajectory.

Simulation results show a good similarity between the two models and verify both longitudinal and lateral behaviors of the WMR. This demonstrates the effectiveness of the developed model using the robotic approach and proves that it is sufficiently precise for the design of control schemes.

The motivation to adopt this robotic approach compared to conventional methods is the fact that it makes it possible to obtain models with a reduced number of operations. Furthermore, it allows the facility of implementation by numerical or symbolical programming. This work serves as a reference link for extending this methodology to other types of mobile robots.