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Online suboptimal control of linearized models

Costanza, Vicente et al · Taylor & Francis · 2014

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A novel approach to approximately solving the restricted-control LQR problem online is substantiated and applied in two case-studies. The first example is a one-dimensional system whose exact solution is known. The other one refers to the temperature control of a metallic strip at the exit of a multi-stand rolling mill. The new (online-feedback) strategy employs a convenient version of the gradient method, where partial derivatives of the cost are taken with respect to the final penalization matrix coefficients and to the switching times where the control (de)saturates. The calculations are based on exact algebraic formula, which do not involve trajectory simulations, and so reducing in principle the computational effort associated with receding horizon or nonlinear programming methods. Fil: Costanza, Vicente. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina Fil: Rivadeneira Paz, Pablo Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina

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APA 7

Costanza, V. E. A. (2014). Online suboptimal control of linearized models. http://hdl.handle.net/11336/9251

MLA

Costanza, Vicente et al. "Online suboptimal control of linearized models." 2014. http://hdl.handle.net/11336/9251.

Chicago

Costanza, Vicente et al. 2014. "Online suboptimal control of linearized models.". http://hdl.handle.net/11336/9251.

Harvard

Costanza, V. E. A. 2014, Online suboptimal control of linearized models, Taylor & Francis, available at: http://hdl.handle.net/11336/9251 [Accessed 6 Aug. 2026].

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Title
Online suboptimal control of linearized models
Author / contributors
Costanza, Vicente et al
Publisher
Taylor & Francis
Publication year
2014
ISSN
2164-2583
ISSN
2164-2583
Language
English

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