Predefined lookup table inspired direct power control techniques have been used mostly for active front end rectifiers. As an intransigent switching pattern is followed here, the effectiveness of the converter is hampered when the operating parameters change. Apart from that, the switching table design is attributed only to the sign of power demand. In this work, the magnitude of the power demand along with its sign is considered for the selection of the switching vector. The phase angle of the grid voltage vector is estimated using the virtual flux technique. The magnitude of active and reactive powers transferred from the grid to the converter depends on the switching vector of the converter and the phase angle of the grid voltage vector. Conventional methods of Direct Power Control have used 12 sector-based divisions. The switching vector is selected depending on the 30 slabs to which the grid voltage vector belongs. With the advent of high-speed microcontrollers, it is possible to improve the accuracy of the conventional DPC with increased resolution in the switching vector selection. So, in this work, one complete cycle of the grid voltage vector is divided into 18 sectors instead of 12 sectors to locate the grid voltage vector more accurately. Finally, a redesigned algorithm is customed to select the most suited vector that meets the power demands of the active front end rectifier at that particular phase angle. The feasibility of the proposed technique is verified with MATLAB simulations and experiments conducted in the laboratory.

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Research methodology This study aims to investigate the factors that contribute to the overall tour experience and services provided by Top Tier Holidays. The study is mixed in nature, and the researchers have used analytical tools to analyse the data factually. Multiple regression using MS Excel is used in the study. Case overview/synopsis This case is based on the experiences of a real-life travel and tour company located in New Delhi, India. The case helps understand regression analysis to identify independent variables significantly impacting the tour experience. The CEO of the company is focused on improving the overall customer experience. The CEO has identified six principal determinants (variables) applicable to tour companies’ success. These variables are hotel experience, transportation, cab driver, on-tour support, itinerary planning and pricing. Multiple regression analysis using Microsoft Excel is conducted on the above determinants (the independent variables) and the overall tour experience (the dependent variable). This analysis would help identify the relationship between the independent and dependent variables and find the variables that significantly impact the dependent variable. This case also helps us appreciate the importance of various parameters that affect the overall customer tour experience and the challenges a tour operator company faces in the current competitive business environment. Complexity academic level This case is designed for discussion with the undergraduate courses in business management, commerce and tourism management programmes. The case will build up readers’ understanding of linear regression with multiple variables. It shows how multiple linear regression can help companies identify the significant variables affecting business outcomes.

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