Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
86 tokens/sec
Gemini 2.5 Pro Premium
43 tokens/sec
GPT-5 Medium
19 tokens/sec
GPT-5 High Premium
30 tokens/sec
GPT-4o
93 tokens/sec
DeepSeek R1 via Azure Premium
88 tokens/sec
GPT OSS 120B via Groq Premium
441 tokens/sec
Kimi K2 via Groq Premium
234 tokens/sec
2000 character limit reached

Continuous Hands-off Control by CLOT Norm Minimization (1611.02071v1)

Published 7 Nov 2016 in cs.SY

Abstract: In this paper, we consider hands-off control via minimization of the CLOT (Combined L-One and Two) norm. The maximum hands-off control is the L0-optimal (or the sparsest) control among all feasible controls that are bounded by a specified value and transfer the state from a given initial state to the origin within a fixed time duration. In general, the maximum hands-off control is a bang-off-bang control taking values of +1, -1, and 0. For many real applications, such discontinuity in the control is not desirable. To obtain a continuous but still relatively sparse control, we propose to use the CLOT norm, a convex combination of L1 and L2 norms. We show by numerical simulation that the CLOT control is continuous and much sparser (i.e. has longer time duration on which the control takes 0) than the conventional EN (elastic net) control, which is a convex combination of L1 and squared L2 norms.

Citations (11)

Summary

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

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube