Adaptive Synthesized Control for Solving the Optimal Control Problem
نویسندگان
چکیده
The development of artificial intelligence systems assumes that a machine can independently generate an algorithm actions or control system to solve the tasks. To do this, must have formal description problem and possess computational methods for solving it. This article deals with optimal control, which is main task in systems, insofar as all being developed be from point view certain criterion. However, there are difficulties implementing resulting modes. paper considers extended formulation problem, implies creation such would necessary properties its practical implementation. it, adaptive synthesized approach based on use numerical learning proposed. Such moves object, optimally changing position stable equilibrium presence some initial uncertainty. As result, possible controls, one chosen less sensitive changes state. example, quadcopter complex phase constraints considered. this according proposed approach, synthesis firstly solved obtain state space using method symbolic regression. After that, positions searched particle swarm optimization source functional statement. It shown allows generating automatically by computer, basing statement then directly it onboard far stabilization has already been introduced.
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ژورنال
عنوان ژورنال: Mathematics
سال: 2023
ISSN: ['2227-7390']
DOI: https://doi.org/10.3390/math11194035