NDLI: Multi-step prediction optimal control for a scalar linear system with additive Cauchy noise

Content Provider	IEEE Xplore Digital Library
Author	Speyer, J.L. Idan, M. Fernandez, J.
Copyright Year	2010
Description	Author affiliation: Mechanical and Aerospace Engineering, University of California, Los Angeles, 90095-1597, USA (Speyer, J.L.; Fernandez, J.) \|\| Aerospace Engineering, Technion - Israel Institute of Technology, Haifa, Israel, 32000 (Idan, M.)
Abstract	A multi-step predictive optimal control scheme is developed for scalar discrete linear dynamic systems driven by Cauchy distributed process and measurement noises. Although the Cauchy densities that model the process and measurement noise have an undefined first moment and an infinite second moment, the probability density function conditioned on linear noisy measurements does have a finite mean and variance. For the control problem a cost criterion should be defined for which the unconditional expectation of this criterion with respect to the Cauchy densities exists. The cost criterion chosen is functionally similar to the Cauchy density. Although a dynamic programming solution for this criterion is not yet transparent, for the multistage problem an optimal controller is determined that at each time stage minimizes the unconditional expected cost to some terminal time. Numerical results are shown for this m-step predictive optimal control scheme. An essential difference between the proposed controller and one designed for Gaussian noises is that large measurement noises do not produce large control responses, although large and impulsive process noises do induce controls needed for regulation.
Starting Page	4157
Ending Page	4164
File Size	289317
Page Count	8
File Format	PDF
ISBN	9781424477456
ISSN	07431546
e-ISBN	9781424477463
DOI	10.1109/CDC.2010.5717152
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Noise Noise measurement Predictive models Optimal control Stochastic processes Leg Numerical models
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Modeling and Simulation

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Optimal control for a scalar one-step linear system with additive Cauchy noise

The two-state estimator for linear systems with additive measurement and process Cauchy noise

A stochastic controller for vector linear systems with additive cauchy noises

Optimal Tracking Problem for Stochastic Linear Using Exponential Performance Criterion

Scenario-based approach to stochastic linear predictive control

Optimal ensemble control of stochastic linear systems

Finite horizon MPC for systems in innovation form

Scenario-based stochastic model predictive control for dynamic option hedging

Multi-step-ahead multivariate predictors: A comparative analysis

Multi-step prediction optimal control for a scalar linear system with additive Cauchy noise

Similar Documents

Optimal control for a scalar one-step linear system with additive Cauchy noise

The two-state estimator for linear systems with additive measurement and process Cauchy noise

A stochastic controller for vector linear systems with additive cauchy noises

Optimal Tracking Problem for Stochastic Linear Using Exponential Performance Criterion

Scenario-based approach to stochastic linear predictive control

Optimal ensemble control of stochastic linear systems

Finite horizon MPC for systems in innovation form

Scenario-based stochastic model predictive control for dynamic option hedging

Multi-step-ahead multivariate predictors: A comparative analysis

Multi-step prediction optimal control for a scalar linear system with additive Cauchy noise