Constrained linear state estimation - A moving horizon approach

Automatica

Volumn 37, Issue 10, 2001, Pages 1619-1628

  Rao, Christopher V ^a   Rawlings, James B ^b   Lee, Jay H ^c  

^a University of California at Berkeley   (United States)

^b University of Wisconsin Madison   (United States)

^c Georgia Institute of Technology   (United States)

Author keywords

Constraints; Optimization; Stability; State estimation

Indexed keywords

CONSTRAINT THEORY; CONTROL SYSTEM ANALYSIS; LINEAR CONTROL SYSTEMS; MATHEMATICAL MODELS; OPTIMIZATION; SYSTEM STABILITY;

MOVING HORIZON APPROACH;

STATE ESTIMATION;

EID: 0035480348     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0005-1098(01)00115-7     Document Type: Article

References (23)

1. Efficient solution of dynamic optimization and NMPC problems
2. Monotonicity and stabilizability properties of solutions of the Riccati difference equation: Propositions, lemmas, theorems, fallacious conjectures and counterexamples
3. Smoothing for linear and nonlinear dynamic systems
4. Riccati equation in optimal filtering of nonstabilizable systems having singular state transition matrices
5. An algorithm for quadratic programming
6. Optimal infinite-horizon feedback laws for a general class of constrained discrete-time systems: Stability and moving-horizon approximations
7. Recent advances in model predictive control and other related are as
8. Nonlinear model predictive control: An assessment
9. Constrained model predictive control: Stability and optimality
10. Nonlinear moving horizon state estimation
11. Receding horizon recursive state estimation
12. Constrained process monitoring: A moving horizon approach
13. Nonlinear moving horizon estimation
14. Maximum likelihood estimates of linear dynamic systems
15. A moving horizon-based approach for least-squares state estimation
16. Sufficient statistics in the optimum control of stochastic systems
17. Abstract dynamic programming models under commutativity conditions