Title :
A neural network regulator for turbogenerators
Author :
Wu, Q.H. ; Hogg, B.W. ; Irwin, G.W.
Author_Institution :
Dept. of Electr. Eng., Queen´´s Univ. of Belfast, UK
fDate :
1/1/1992 12:00:00 AM
Abstract :
A neural network (NN) based regulator for nonlinear, multivariable turbogenerator control is presented. A hierarchical architecture of an NN is proposed for regulator design, consisting of two subnetworks which are used for input-output (I-O) mapping and control, respectively, based on the back-propagation (BP) algorithm. The regulator has the flexibility for accepting more sensory information to cater to multi-input, multioutput systems. Its operation does not require a reference model or inverse system model and it can produce more acceptable control signals than are obtained by using sign of plant errors during training I-O mapping of turbogenerator systems using NNs has been investigated and the regulator has been implemented on a complex turbogenerator system model. Simulation results show satisfactory control performance and illustrate the potential of the NN regulator in comparison with an existing adaptive controller
Keywords :
machine control; multivariable control systems; neural nets; nonlinear control systems; turbogenerators; I-O mapping; MIMO systems; back-propagation; control performance; hierarchical architecture; multivariable turbogenerator control; neural network regulator; sensory information; subnetworks; turbogenerators; Adaptive control; Algorithm design and analysis; Control system synthesis; Control systems; Inverse problems; Neural networks; Programmable control; Regulators; Robust control; Turbogenerators;
Journal_Title :
Neural Networks, IEEE Transactions on
