DESIGN OF STABILIZING NEURAL NETWORK CONTROLLER FOR A CLASS OF NONLINEAR SYSTEMS

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ROUHANI S.M.; MENHAJ M.B.

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Journal: AMIRKABIR Year:2001 | Volume:12 | Issue:48 Page(s): 295-302

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Information Journal Paper

Title

DESIGN OF STABILIZING NEURAL NETWORK CONTROLLER FOR A CLASS OF NONLINEAR SYSTEMS

Author(s)

ROUHANI S.M. | MENHAJ M.B. | Issue Writer Certificate

Keywords

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Abstract

A novel design procedure is presented that determines the weight matrices of a neural network conroller for a class of nonlinear multi-input systems. The plant is a linear system supposed to bounded inputs. In contrast to concentional recursive training methods, the novel design method is based upon an one-parameter optimization which directly specifies the weight matrices. The stability of the closed loop system is guaranteed analytically.

Cites

A METHOD FOR NEURAL ADAPTIVE CONTROL OF NONLINEAR SYSTEMS AND ITS STABILITY ANALYSIS

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APA: Copy

ROUHANI, S.M., & MENHAJ, M.B.. (2001). DESIGN OF STABILIZING NEURAL NETWORK CONTROLLER FOR A CLASS OF NONLINEAR SYSTEMS. AMIRKABIR, 12(48), 295-302. SID. https://sid.ir/paper/784/en

Vancouver: Copy

ROUHANI S.M., MENHAJ M.B.. DESIGN OF STABILIZING NEURAL NETWORK CONTROLLER FOR A CLASS OF NONLINEAR SYSTEMS. AMIRKABIR[Internet]. 2001;12(48):295-302. Available from: https://sid.ir/paper/784/en

IEEE: Copy

S.M. ROUHANI, and M.B. MENHAJ, “DESIGN OF STABILIZING NEURAL NETWORK CONTROLLER FOR A CLASS OF NONLINEAR SYSTEMS,” AMIRKABIR, vol. 12, no. 48, pp. 295–302, 2001, [Online]. Available: https://sid.ir/paper/784/en

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