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
Massimiliano d’Angelo;
2019-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
