A calibration approach based on Takagi–Sugeno fuzzy inference system for digital electronic compasses

Recently, the development of industrial processes brought on the outbreak of technologically complex systems. This development generated the necessity of research relative to the mathematical techniques that have the capacity to deal with project complexities and validation. Fuzzy models have been receiving particular attention in the area of nonlinear systems identification and analysis due to it is capacity to approximate nonlinear behavior and deal with uncertainty. A fuzzy rule-based model suitable for the approximation of many systems and functions is the Takagi–Sugeno (TS) fuzzy model. TS fuzzy models are nonlinear systems described by a set of if then rules which gives local linear representations of an underlying system. Such models can approximate a wide class of nonlinear systems. In this paper a performance analysis of a system based on TS fuzzy inference system for the calibration of electronic compass devices is considered. The contribution of the evaluated TS fuzzy inference system is to reduce the error obtained in data acquisition from a digital electronic compass. For the reliable operation of the TS fuzzy inference system, adequate error measurements must be taken. The error noise must be filtered before the application of the TS fuzzy inference system. The proposed method demonstrated an effectiveness of 57% at reducing the total error based on considered tests.

Research highlights
► It is necessary to use the power of the Takagi-Sugeno system to approximate the behavior of the error function of the compass … exploiting the system’s interpolation characteristics.
► There is a nonlinear relationship between the compass reading, the true value, scale factors and needle declination angles in the reading domain.
► The proposed method presented an efficiency of 57% for the reduction of average of absolute error values, which is an unexpectedly high efficiency given the simplicity with which was chosen to implement the TS fuzzy system.