Work

Performance improvement of discrete‐time linear‐quadratic regulators applied to uncertain linear systems using the Tikhonov regularization method

Year: 2026

Type: article

Abstract: The linear‐quadratic regulator (LQR) problem of optimal control of an uncertain discrete‐time linear system (DTLS) is revisited in this paper from the perspective of Tikhonov regularization. We show that an optimally chosen regularization parameter reduces, compared to the classical LQR, the values of a scalar error function, as well as the cost function. The scalar regularization parameter can be calculated using a standard parameter choice method. Simulations confirm performance improvement when this regularized control signal is applied to a DTLS subject to a varying sampling rate.

Source: Asian Journal of Control

DOI: 10.1002/asjc.70094

Authors: Fernando Pazos, Amit Bhaya

Institutions: Universidade Federal do Rio de Janeiro, National University of Avellaneda

Language: English

Topic: Advanced Control Systems Optimization

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,850

Funders: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro