%0 Journal Article
	%A Magdi M. Nabi and  Ding-Li Yu
	%D 2014
	%J International Journal of Mechanical and Mechatronics Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 91, 2014
	%T Nonlinear Adaptive PID Control for a Semi-Batch Reactor Based On an RBF Network
	%U https://publications.waset.org/pdf/9999262
	%V 91
	%X Control of a semi-batch polymerization reactor using
an adaptive radial basis function (RBF) neural network method is
investigated in this paper. A neural network inverse model is used to
estimate the valve position of the reactor; this method can identify the
controlled system with the RBF neural network identifier. The
weights of the adaptive PID controller are timely adjusted based on
the identification of the plant and self-learning capability of RBFNN.
A PID controller is used in the feedback control to regulate the actual
temperature by compensating the neural network inverse model
output. Simulation results show that the proposed control has strong
adaptability, robustness and satisfactory control performance and the
nonlinear system is achieved.

	%P 1260 - 1265