DocumentCode :
1943415
Title :
Improved Lagrange Nonlinear Programming Neural Networks for Inequality Constraints
Author :
Huang, Yuancan ; Yu, Chuang
Author_Institution :
Yuancan Huang, Beijing
fYear :
2007
fDate :
12-17 Aug. 2007
Firstpage :
962
Lastpage :
966
Abstract :
By redefining multiplier associated with inequality constraint as a positive definite function of the originally-defined multiplier, u2 j ,i = 1,2, ----, m, say, the nonnegative constraints imposed on inequality constraints in Karush-Kuhn-Tucker necessary conditions are removed completely. Hence it is no longer necessary to convert inequality constraints into equality constraints by slack variables in order to reuse those results concerned only with equality constraints. Utilizing this technique, improved Lagrange nonlinear programming neural networks are devised, which handle inequality constraints directly without adding slack variables. Then the local stability of the proposed Lagrange neural networks is analyzed rigourously with Liapunov´s first approximation principle, and its convergence is discussed deeply with LaSalle´s invariance principle. Finally, an illustrative example shows that the proposed neural networks can effectively solve the nonlinear programming problems.
Keywords :
approximation theory; neural nets; nonlinear programming; Karush-Kuhn-Tucker condition; LaSalle invariance principle; Lagrange nonlinear programming neural network; Liapunov approximation principle; equality constraint; nonnegative inequality constraint; positive definite function; slack variable; Circuit stability; Convergence; Functional programming; Intelligent robots; Lagrangian functions; Linear programming; Neural networks; Quadratic programming; Robot programming; Stability analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
ISSN :
1098-7576
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
Type :
conf
DOI :
10.1109/IJCNN.2007.4371088
Filename :
4371088
Link To Document :
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