The paper is devoted to an emerging trend in control—a machine learning control. Despite the popularity of idea learning, there are various interpretations this concept, and urgent need for its strict mathematical formalization. An attempt formalize concept presented paper. concepts unknown function, work area, training set introduced, a formulation problem presented. Based on formulation, cont...

The determination of minimum-fuel or minimum-time space trajectories has been pursued for decades, using different methods of solution. This work illustrates some symmetry properties that hold for optimal space trajectories and can considerably simplify their determination. The existence of symmetry properties is demonstrated in the presence of certain boundary conditions for the problem of int...

In this contribution two approaches for calculating optimal trajectories for highly automated vehicles are presented and compared. The first one is based on a non-linear vehicle model, used for evaluation. The second one is based on a simplified model and can be implemented on a current ECU. In usual driving situations both approaches show very similar results. Keywords—Trajectory planning, dir...

Using the method of quantum trajectories we show that a known pure state can be optimally monitored through time when subject to a sequence of discrete measurements. By modifying the way we extract information from the measurement apparatus we can minimise the average algorithmic information of the measurement record, without changing the unconditional evolution of the measured system. We deene...

We consider the problem of determining sensor trajectories in the bearings-only tracking of an uncertain target. This work differs from previous research in that we allow the target dynamics to be both uncertain and random; and also consider multi-sensor scenarios. The basis of our technique is to control a measure of estimation error based on the Posterior Cramér-Rao lower bound (PCRLB), and w...