An algebraic, distributed state observer for continuous‐ and discrete‐time linear time‐invariant systems with time‐varying communication graphs

Generalized parameter estimation-based observers: Application to power systems and chemical–biological reactors

(2021) Romeo Ortega et al.   AUTOMATICA

A simple finite-time distributed observer design for linear time-invariant systems

(2020) Haik Silm et al.   SYSTEMS & CONTROL LETTERS

Reduced order finite time observers and output feedback for time-varying nonlinear systems

(2020) Frédéric Mazenc et al.   AUTOMATICA

Distributed Observers for LTI Systems With Finite Convergence Time: A Parameter-Estimation-Based Approach

(2020) Romeo Ortega et al.   IEEE TRANSACTIONS ON AUTOMATIC CONTROL

Distributed state estimation for discrete-time linear time invariant systems: A survey

(2019) Francisco F.C. Rego et al.   ANNUAL REVIEWS IN CONTROL

Finite‐time consensus of Euler‐Lagrange agents without velocity measurements via energy shaping

(2019) Emmanuel Cruz‐Zavala et al.   INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL

Adaptive control of linear multivariable systems using dynamic regressor extension and mixing estimators: Removing the high-frequency gain assumptions

(2019) Romeo Ortega et al.   AUTOMATICA

Distributed Observers for LTI Systems

(2018) Aritra Mitra et al.   IEEE TRANSACTIONS ON AUTOMATIC CONTROL

A note on distributed finite-time observers

(2018) Haik Silm et al.   IEEE TRANSACTIONS ON AUTOMATIC CONTROL

Performance Enhancement of Parameter Estimators via Dynamic Regressor Extension and Mixing*

(2017) Stanislav Aranovskiy et al.   IEEE TRANSACTIONS ON AUTOMATIC CONTROL

Design of Distributed LTI Observers for State Omniscience

(2017) Shinkyu Park et al.   IEEE TRANSACTIONS ON AUTOMATIC CONTROL

A parameter estimation approach to state observation of nonlinear systems

(2015) Romeo Ortega et al.   SYSTEMS & CONTROL LETTERS

Reaching a Consensus in a Dynamically Changing Environment: A Graphical Approach

(2008) Ming Cao et al.   SIAM JOURNAL ON CONTROL AND OPTIMIZATION