Work

Computation of feedback control laws based on switched tracking of demonstrations

Year: 2024

Type: article

Abstract: A common approach in robotics is to learn tasks by generalizing from special cases given by a so-called demonstrator. In this paper, we apply this paradigm and present an algorithm that uses a demonstrator (typically given by a trajectory optimizer) to automatically synthesize feedback controllers for steering a system described by ordinary differential equations into a goal set. The resulting feedback control law switches between the demonstrations that it uses as reference trajectories. In comparison to the direct use of trajectory optimization as a control law, for example, in the form of model predictive control , this allows for a much simpler and more efficient implementation of the controller. The synthesis algorithm comes with rigorous convergence and optimality results, and computational experiments confirm its efficiency.

Source: European Journal of Control

DOI: 10.1016/j.ejcon.2024.101118

Authors: Jiří Fejlek, Stefan Ratschan

Institutions: Czech Academy of Sciences, Czech Academy of Sciences, Institute of Computer Science, Czech Technical University in Prague

Language: English

Topic: Advanced Control Systems Optimization

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,850

Funder: Grantová Agentura České Republiky