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The Chapter is focusing in the area of the Electrically-powered Unmanned Aerial Vehicles (UAVs) in association to bounded sensor noise. The increased requirements for airworthiness and safety of such vehicles have resulted in the requirement of improving the analytical methods for subsystem level mathematical modelling, such as for example the electrical propulsion system. The Takagi-Sugeno fuzzy inference has been formulated in the context of bounded multi-sensor errors for a range of error classes. The modelled system is an electrical propulsion system together with the associated sensor boundaries in relation to a typical UAV operation. Unmanned aerial vehicles have been used in various operational conditions where other vehicles fail to operate. UAVs have been used to inspect hazardous areas such as flooded areas, earthquake areas, and generally areas that may have a high risk of radioactive contaminants. The immediate result of the effective use of UAVs is reducing the risk of endangering human lives while still capable of operating safely and efficiently. This chapter addresses the issue of sensor operational boundaries and the UAV’s electrical thruster parametric variation due to altitude variations. UAVs normally operate over a range of altitudes Kladis et al. (2010) depending on their operational role. Hence, these can be exposed to a range of temperature conditions which can affect their normal operation. This chapter addresses this specific consideration which can have airworthiness implications, and focuses on the description of the electrical permanent magnet direct current thrusters in the context of UAVs and operations . The UAV’s propulsion options can vary depending on the user and operational requirements, however the focal point for the work described in this chapter is for an electrical thruster system. Such systems being supplied from a fuel cell are described in more detail in Karunarathne et al. (2007). In particular, the work in Karunarathne et al. (2007), describes for a given example UAV operation the effectiveness of the electric propulsion option together with the importance of a sophisticated power management system utilising intelligent based methods. In Miller (2004), the propulsion system options are described within the context of power and energy and thus assist towards the importance of electro-mechanical systems for propulsion. In Ehsani et al. (2005), the authors

Sugeno Inference Perturbation Analysis for Electric Aerial Vehicles