Release R20210710 (decenter-1.1.0)

Release source code can be found here.

New release, which features:

Documentation:

• Updated kalmanOneStepLTI: added efficient implementation of the sparse matrix equation solver for the one-step filter gain synthesis (LTI);

• Updated kalmanFiniteHorizonLTI: added efficient implementation of the sparse matrix equation solver for the finite-horizon filter gain synthesis (LTI);

• Updated LQROneStepLTI: added efficient implementation of the sparse matrix equation solver for the one-step LQR gain synthesis (LTI);

• Updated LQRFiniteHorizonLTI: added efficient implementation of the sparse matrix equation solver for the finite-horizon LQR gain synthesis (LTI);

• Updated LQROneStepLTV: added efficient implementation of the sparse matrix equation solver for the one-step LQR synthesis (LTV);

• Added kalmanCentralizedLTV: for the computation of centralized filter gains for an LTV system;

• Added kalmanOneStepLTV: for the computation of distributed filter gains for an LTV system using the one-step method;

• Added kalmanFiniteHorizonLTV: for the computation of distributed filter gains for an LTV system using the finite-horizon method;

Tutorials:

• Added tutorial on decentralized Kalman filter synthesis using the one-step for LTV systems. See Tutorial on decentralized Kalman filter synthesis using the one-step method.;

• Added tutorial on decentralized Kalman filter synthesis using the finite-horizon method for LTV systems. See Tutorial on decentralized Kalman filter synthesis using the finite-horizon method.

Examples:

• Added application of decentralized estimation to the N-tank network, using the one-step and finite-horizon methods. See Decentralized estimation of nonlinear N-tank network;