Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems

The increasing energy demand and the target to reduce environmental pollution make it essential to use efficient and environment-friendly renewable energy systems. One of these systems is the Photovoltaic (PV) system which generates energy subject to variation in environmental conditions such as temperature and solar radiations. In the presence of these variations, it is necessary to extract the maximum power via the maximum power point tracking (MPPT) controller. This paper presents a nonlinear generalized global sliding mode controller (GGSMC) to harvest maximum power from a PV array using a DC-DC buck-boost converter. A feed-forward neural network (FFNN) is used to provide a reference voltage. A GGSMC is designed to track the FFNN generated reference subject to varying temperature and sunlight. The proposed control strategy, along with a modified sliding mode control, eliminates the reaching phase so that the sliding mode exists throughout the time. The system response observes no chattering and harmonic distortions. Finally, the simulation results using MATLAB/Simulink environment demonstrate the effectiveness, accuracy, and rapid tracking of the proposed control strategy. The results are compared with standard results of the nonlinear backstepping controller under abrupt changes in environmental conditions for further validation

Understanding Mobile Tourism Shopping in Pakistan: An Integrating Framework of Innovation Diffusion Theory and Technology Acceptance Model

Consumer adoption of mobile-based tourism shopping is an emerging but overlooked area in tourism research. Given the paybacks and potential scope of this new channel, this study attempts to bridge the gap by proposing a multimediation model investigating mobile tourism shopping (MTS) in a developing country, Pakistan. In particular, we applied structural equation modeling through partial-least-squares structural equation modeling (PLS-SEM) on 396 responses collected from mobile respondents who recently purchased tourism products using a mobile device(s). It was discovered that social presence, directly and indirectly, influences tourist intentions towards MTS. The results further show that the tourists’ perception of compatibility and relative advantages of MTS have insignificant influence on their intention to accept a mobile device(s) for tourism shopping. The findings and implications of the study furnish new vistas to research discourse and managerial significance. Economically, this research contributes to knowledge that could increase income and create jobs in the host country

Robust Integral Sliding Mode Control Design for Stability Enhancement of Under-actuated Quadcopter

In this paper, a robust backstepping integral sliding mode control (RBISMC) technique is designed for the flight control of a quadcopter, which is an under-actuated nonlinear system. First, the mathematical model of this highly coupled and under-actuated system is described in the presence of dissipative drag forces. Second, a robust control algorithm is designed for the derived model to accurately track the desired outputs while ensuring the stability of attitude, altitude and position of the quadcopter. A step by step mathematical analysis, based on the Lyapunov stability theory, is performed that endorses the stability of both the fully-actuated and under-actuated subsystems of the aforementioned model. The comparison of proposed RBISMC control algorithm, with fraction order integral sliding mode control (FOISMC), affirms the enhanced performance in terms of faster states convergence, improved chattering free tracking and more robustness against uncertainties in the system