{'fraction_non_alphanumeric': 0.020538243626062325, 'fraction_numerical': 0.0, 'mean_word_length': 5.143478260869565, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
In-flight Efficient Controller Auto-tuning using a Pair of UAVs

In the paper, a pair of auto-tuning methods for fixed-parameter controllers is presented, in application to multirotor unmanned aerial vehicles (UAVs) control. In both cases, the automatized process of searching the best altitude controller parameters is carried out with the use of a modified golden-search method, for a selected cost function, during the flight of a pair of UAVs. All the calculations are performed in real-time in the iterative manner using only basic sensory information available concerning current altitude information for a pair of UAVs. The auto-tuning process of the controller is characterized by neglectfully low computational demand, and the parameters are obtained rapidly with no dynamic model of a UAV needed. In both methods, by using a pair of UAVs in tuning process, the level of control performance can be increased, what has been proved by means of multiple outdoor experiments. The first method increases precision of the obtained controller parameters by averaging sensory information over a pair of UAVs, whereas in the second, by exchanging measurement information between the units, the search space is explored faster. The latter is of special importance when seeking the best controller parameters, what is especially expected when a limited experiment duration of multirotor UAVs is taken into account.