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A comparison between gain-scheduling linear quadratic regulator and model predictive control for a manipulator with flexible components

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Author(s):
Colombo, Fernanda Thais ; da Silva, Maira Martins
Total Authors: 2
Document type: Journal article
Source: PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING; v. 236, n. 7, p. 9-pg., 2022-04-05.
Abstract

Dynamic performance and energy efficiency can be improved by reducing the inertia of mechanical systems. However, the components of such a system may be flexible and, inevitably, subject to vibrations. Moreover, the relative motion between flexible components leads to time-varying boundary conditions characterizing configuration-dependent dynamics. Since robust controllers may be conservative for this problem, adaptive controllers should be considered since they can cope with performance design requirements. In this work, we present a comparison between a linear quadratic regulator gain-scheduling control and an adaptive model predictive control for a flexible industrial Cartesian manipulator with configuration-dependent dynamics. This study takes the system stability and the use of bounded actuation into account. Numerical results demonstrate that the adaptive model predictive control strategy achieved better performance than the linear quadratic regulator gain scheduled. Also, in applications with tighter actuation bounds, the difference between the performance of both approaches is even higher, reinforcing the model predictive control capability of dealing with limited actuation. (AU)

FAPESP's process: 18/22760-0 - Control of parallel planar manipulators with flexible links
Grantee:Fernanda Thaís Colombo
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 18/21336-0 - Towards high speed parallel kinematic machines, Phase II: instrumentation, modeling and control of a flexible manipulator
Grantee:Maira Martins da Silva
Support Opportunities: Regular Research Grants