Ημερολόγιο Εκδηλώσεων

Abstract: A novel auto-tuning approach for finding locally-best parameters of controllers on-board of unmanned aerial vehicles (UAVs) will be presented. The controller tuning is performed fully autonomously during flight on the basis of predefined ranges of controller parameters. Required controller properties may be simply interpreted by a cost function, which is involved in the optimization process. For example, the sum of absolute values of the tracking error samples or performance indices, including weighed functions of control signal samples, can be penalized to achieve very precise position control, if required. The proposed method relies on a zero-order optimization search technique fitted into bootstrap sequences, enabling one to obtain a global minimizer for a unimodal cost function. The approach is characterized by an extremely low computational complexity and does not require any UAV dynamics model (just periodical measurements from basic on-board sensors) to obtain proper tuning of a controller. In addition to outlining the complete, and yet simple, theoretical background of the method, an experimental verification in real-world outdoor conditions will provided with relation to multiple experiments, applications and results.