Accurate process modeling is occasionally difficult. In such situations, auto-tuning methods enable the design of suitable controllers based on experimental data and predefined mathematical approaches. Fractional order PIDs have recently emerged as a generalization of the standard PID controller, but auto-tuning methods for these controllers are scarce. In this paper, three sine-test based methodologies are presented from a control engineer's perspective consisting of novel Sine-Test, FO-KC and FO-ZN methods, with clear design and implementation guidelines. The approaches are exemplified on a highly nonlinear experimental platform. An in depth comparison is performed based on experimental closed loop system performance for wide operating areas, tuning effort and complexity, with a focus on the suitability for industrial applications. The study aims at providing a solid foundation for practitioners that desire to explore auto-tuning possibilities, presenting tuning workflows and implementation guidelines, while also considering the challenges associated with real-life process.