摘要
0 INTRODUCTIONWithextensiveuseofartificialneuralnetworkinnonlinearcontrolsystems,itbecomesveryimportanttostudythestabilityof...
Untanpreeda presented a training algorithm based on BP [1] , which guarantees the closed loop stability for a class of widely used Neural network control systems. However, it has some shortcomings, such as insufficient stable condition, low efficiency and frequent convergence of parameters to a local minimum. A new training algorithm based on Alopex is proposed to ensure sufficient stability, and overcome some of the shortcomings.