The paper concerns the Linear Quadratic non- Gaussian (LQnG) sub-optimal control problem when the input signal travels through an unreliable network, namely a Gilbert- Elliot channel. In particular, the control input packet losses are modeled by a two-state Markov chain with known transition probability matrix, and we assume that the moments of the non- Gaussian noise sequences up to the fourth order are known. By mean of a suitable rewriting of the system through an output injection term, and by considering an augmented system with the second-order Kronecker power of the measurements, a simple solution is provided by substituting the Kalman predictor of the LQG control law with a quadratic optimal predictor. Numerical simulations show the effective ness of the proposed method.
LQ non-Gaussian Regulator with Markovian Control / Battilotti, Stefano; Cacace, Filippo; D'Angelo, Massimiliano; Germani, Alfredo; Sinopoli, Bruno. - In: IEEE CONTROL SYSTEMS LETTERS. - ISSN 2475-1456. - 3:3(2019), pp. 679-684. [10.1109/LCSYS.2019.2916287]
LQ non-Gaussian Regulator with Markovian Control
Stefano Battilotti;Massimiliano d’Angelo
;Alfredo Germani;
2019
Abstract
The paper concerns the Linear Quadratic non- Gaussian (LQnG) sub-optimal control problem when the input signal travels through an unreliable network, namely a Gilbert- Elliot channel. In particular, the control input packet losses are modeled by a two-state Markov chain with known transition probability matrix, and we assume that the moments of the non- Gaussian noise sequences up to the fourth order are known. By mean of a suitable rewriting of the system through an output injection term, and by considering an augmented system with the second-order Kronecker power of the measurements, a simple solution is provided by substituting the Kalman predictor of the LQG control law with a quadratic optimal predictor. Numerical simulations show the effective ness of the proposed method.File | Dimensione | Formato | |
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