Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
169 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Discrete Adaptive Control Allocation (2101.10675v1)

Published 26 Jan 2021 in eess.SY and cs.SY

Abstract: The main purpose of a control allocator is to distribute a total control effort among redundant actuators. This paper proposes a discrete adaptive control allocator for over-actuated sampled-data systems in the presence of actuator uncertainty. The proposed method does not require uncertainty estimation or persistency of excitation. Furthermore, the presented algorithm employs a closed loop reference model, which provides fast convergence without introducing excessive oscillations. To generate the total control signal, an LQR controller with reference tracking is used to guarantee the outer loop asymptotic stability. The discretized version of the Aerodata Model in Research Environment (ADMIRE) is used as an over-actuated system, to demonstrate the efficacy of the proposed method.

Citations (1)

Summary

We haven't generated a summary for this paper yet.