ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Unscented MPSP for Optimal Control of a Class of Uncertain Nonlinear Dynamic Systems

Mathavaraj, S and Padhi, Radhakant (2019) Unscented MPSP for Optimal Control of a Class of Uncertain Nonlinear Dynamic Systems. In: JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME, 141 (6).

[img] PDF
J_Dyn_Sys_Meas_Cont_Trans_ASME_141-6_065001_2019.pdf - Published Version
Restricted to Registered users only

Download (739kB) | Request a copy
Official URL: https://dx.doi.org/10.1115/1.4042549

Abstract

A new computationally efficient nonlinear optimal control synthesis technique, named as unscented model predictive static programming (U-MPSP), is presented in this paper that is applicable to a class of problems with uncertainties in time-invariant system parameters and/or initial conditions. This new technique is a fusion of two recent ideas, namely MPSP and Riemann-Stieltjes optimal control problems. First, unscented transform is utilized to construct a low-dimensional finite number of deterministic problems. The philosophy of MPSP is utilized next so that the solution can be obtained in a computational efficient manner. The control solution not only ensures that the terminal constraint is met accurately with respect to the mean value, but it also ensures that the associated covariance matrix (i.e., the error ball) is minimized. Significance of U-MPSP has been demonstrated by successfully solving two benchmark problems, namely the Zermelo problem and inverted pendulum problem, which contain parametric and initial condition uncertainties.

Item Type: Journal Article
Additional Information: The copyright for this article belongs to ASME.
Department/Centre: Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Depositing User: Ms Ranganayaki RS
Date Deposited: 20 May 2019 06:27
Last Modified: 20 May 2019 06:27
URI: http://eprints.iisc.ac.in/id/eprint/62568

Actions (login required)

View Item View Item