Maton, DariuszEconomou, JohnKhan, IrfanGalvao Wall, DavidCooper, Rob2024-06-092024-06-092024-01-08Maton, Dariusz; Economou, John; Khan, Irfan; Galvao Wall, David; Cooper, Rob (2023). Tuning of a Complementary Orientation Filter Using Velocity Data and a Genetic Algorithm. Cranfield Online Research Data (CORD). Software. https://doi.org/10.17862/cranfield.rd.24807579https://dspace.lib.cranfield.ac.uk/handle/1826/22169The data uploaded here contains the experimental and simulation data used to demonstrate the utility of the optimisation of a complementary orientation filter using a genetic algorithm (GA). Implementation of the GA in MATLAB is provided as well as supporting functions such as the zero velocity update and weighted-relative velocity error metric (W-RVE). The novelty of the work is the optimal tuning of the complementary filter gain using a GA and velocity data of an object moving in the locally level frame. Optimal filter gains are encoded a Takagi-Sugeno (TS) fuzzy inference system with four Gaussian membership functions. This offers a transparent and traceable encoding.CC BY 4.0https://creativecommons.org/licenses/by/4.0/'Orientation filter''Optimisation''IMU''Inertial data''Genetic Algorithm (GA)''MATLAB'Software10.17862/cranfield.rd.24807579