2022
DOI: 10.1007/s40435-022-00980-y
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Generalizing the Letov formula for the discrete-time case

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2023
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Cited by 2 publications
(2 citation statements)
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“…Nonetheless, the key to creating LQR-optimized controllers for real-time applications is largely dependent on the efficient selection of Q and R weighting matrices, which necessarily involve trade-offs and are often tuned based on trial and error [ 20 ]. In addition, improving the efficiency of solving the Riccati algebraic differential equations is considered to be a progressive manifestation of designing LQR controllers [ 21 ]. Evolutionary computation (EC) was proposed as an alternative method to solve such optimization problems [ 22 ].…”
Section: Introductionmentioning
confidence: 99%
“…Nonetheless, the key to creating LQR-optimized controllers for real-time applications is largely dependent on the efficient selection of Q and R weighting matrices, which necessarily involve trade-offs and are often tuned based on trial and error [ 20 ]. In addition, improving the efficiency of solving the Riccati algebraic differential equations is considered to be a progressive manifestation of designing LQR controllers [ 21 ]. Evolutionary computation (EC) was proposed as an alternative method to solve such optimization problems [ 22 ].…”
Section: Introductionmentioning
confidence: 99%
“…In this sens, recent reported works have demonstrated that it is possible to ensure the stability in discrete-time domain for multi-input-multi-output (MIMO) systems. This has been achieved through a generalization of the Letov formula, as mentioned in [3].…”
Section: Introductionmentioning
confidence: 99%