A stochastic controller maximizing the conditional probability density for linear systems with additive cauchy noises

Nati Twito, Moshe Idan, Jason L. Speyer

פרסום מחקרי: פרק בספר / בדוח / בכנספרסום בספר כנסביקורת עמיתים

תקציר

Motivated by the sliding mode control methodology, this work presents a stochastic controller design paradigm for linear system with additive Cauchy distributed noises that expands on previous results addressing single-state systems. The control law utilizes the characteristic function of the time propagated probability density function (pdf) of the system state given measurements that has been derived in recent studies addressing the Cauchy estimation problem. The incentive for the proposed approach is mainly the high numerical complexity of the currently available methods for such systems. The controller performance is evaluated numerically and compared to an alternative approach presented recently and to a Gaussian approximation to the problem. A fundamental difference be-tween the Cauchy and the Gaussian controllers is their superior response to noise outliers. The newly proposed Cauchy controller exhibits similar performance to the previously proposed one, while requiring lower computational effort.

שפה מקוריתאנגלית
כותר פרסום המארחAIAA Scitech 2019 Forum
מזהי עצם דיגיטלי (DOIs)
סטטוס פרסוםפורסם - 2019
אירועAIAA Scitech Forum, 2019 - San Diego, ארצות הברית
משך הזמן: 7 ינו׳ 201911 ינו׳ 2019

סדרות פרסומים

שםAIAA Scitech 2019 Forum

כנס

כנסAIAA Scitech Forum, 2019
מדינה/אזורארצות הברית
עירSan Diego
תקופה7/01/1911/01/19

ASJC Scopus subject areas

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