Title :
A neurocomputing approach for solving the algebraic matrix Riccati equation
Author :
Ham, Fredric M. ; Collins, Emmanuel G.
Author_Institution :
Electr. Eng. Program, Florida Inst. of Technol., Melbourne, FL, USA
Abstract :
This paper presents a neurocomputing approach for solving the algebraic matrix Riccati equation. This approach is able to utilize a good initial condition to reduce the computation time in comparison to standard methods for solving the Riccati equation. The repeated solutions of closely related Riccati equations appears in homotopy algorithms to solve certain problems in fixed-architecture control. Hence, the new approach has the potential to significantly speed-up these algorithms. It also has potential applications in adaptive control
Keywords :
Riccati equations; adaptive control; matrix algebra; neural nets; adaptive control; algebraic matrix Riccati equation; computation time; fixed-architecture control; homotopy algorithms; neurocomputing approach; repeated solutions; Adaptive control; Computer networks; Cost function; Electronic mail; IEEE members; Matrices; Mechanical engineering; Modems; Riccati equations; Robust control;
Conference_Titel :
Neural Networks, 1996., IEEE International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-3210-5
DOI :
10.1109/ICNN.1996.548966
