Title :
Control of unknown nonlinear dynamical systems using CMAC neural networks: structure, stability, and passivity
Author :
Commuri, S. ; Lewis, F.L.
Author_Institution :
Autom. & Robotics Res. Inst., Texas Univ., Arlington, TX, USA
Abstract :
The cerebellar model articulation controller (CMAC) neural network (NN) has advantages over fully connected NNs due to its increased structure. This paper attempts to provide a comprehensive treatment of CMAC NNs in closed-loop control applications. The function approximation capabilities of the CMAC NN are first rigorously established, and novel weight-update laws derived that guarantee the stability of the closed-loop system. The passivity properties of the CMAC under the specified tuning laws are examined and the relationship between passivity and closed-loop stability is derived. The utility of the CMAC NN in controlling a nonlinear system with unknown dynamics is demonstrated through numerical examples
Keywords :
cerebellar model arithmetic computers; closed loop systems; dynamics; function approximation; neurocontrollers; nonlinear dynamical systems; stability; CMAC neural networks; cerebellar model articulation controller; closed-loop control; dynamics; function approximation; nonlinear dynamical systems; passivity; stability; weight-update laws; Associative memory; Automatic control; Control systems; Function approximation; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Robotics and automation; Stability;
Conference_Titel :
Intelligent Control, 1995., Proceedings of the 1995 IEEE International Symposium on
Conference_Location :
Monterey, CA
Print_ISBN :
0-7803-2722-5
DOI :
10.1109/ISIC.1995.525048
