ADAPTIVE CONTROL USING NEURAL NETWORK FOR AN OVERHEAD CRANE SYSTEM WITH UNCERTAINTY OF PAYLOAD MASS

Hai Xuan Le, Tuan Anh Phan, Dinh Duc Nguyen, Tuyen Phong Dinh, Minh Xuan Phan

Abstract


This paper proposes an adaptive control method based on sliding-mode control (SMC) technique for the 3D overhead crane system when considering that the mass of payload unknown. Constant-type and function-type adaptation mechanisms are integrated into control law, in which the mass of payload is considered as a constant-type uncertainty, whereas the uncertain dynamical functionw are estimated by radial basis function neural networks (RBFNNs). The updated law for approximations of the payload mass andweight matrix of the neural network are derived from the Lyapunov theory. The simulation results verified the quality of the proposed controller.

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