Title :
Stable neural control of discrete systems
Author :
Jin, Y. ; Pipe, A.G. ; Winfield, A.
Author_Institution :
Fac. of Eng., Univ. of West England, Bristol, UK
Abstract :
The control of nonlinear discrete systems using neural networks is discussed. The discrete systems discussed have the form yk + 1 = b(yk,...,yk-1)uk + f(yk,...yk-1). Neural networks could be either radial basis functions (RBFs) or cerebellar model articulation controller (CMAC). The stability features are guaranteed, i.e., the errors between the desired values and the actual values are bounded. Theoretical results are strictly proved, and an example is used to explain the theoretical results
Keywords :
cerebellar model arithmetic computers; discrete systems; feedforward neural nets; nonlinear systems; stability; cerebellar model articulation controller; neural control; neural nets; nonlinear discrete systems; radial basis functions; stability; Adaptive control; Computational modeling; Computer networks; Concurrent computing; Control systems; Control theory; Neural networks; Neurons; Nonlinear control systems; Nonlinear systems;
Conference_Titel :
Intelligent Control, 1993., Proceedings of the 1993 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-1206-6
DOI :
10.1109/ISIC.1993.397648
