SYNTHESIS OF NEURAL NETWORK MODEL REFERENCE CONTROLLER FOR AIMING AND STABILIZING SYSTEM
DOI:
https://doi.org/10.20998/2074-272X.2015.5.06Keywords:
neural network control, aiming and stabilization system, nonlinear dynamic object, neuro-controller on the basis of standard model, Model Reference ControllerAbstract
The aim of this work is the synthesis of neural network reference model controller. The synthesis is performed in MATLAB for the problem of control of the aiming and stabilization system for the special equipment of moving objects. This paper presents the synthesis of the neural network reference model controller to meet the given performance characteristics of operation for the aiming and stabilization system for the special equipment of moving objects. Simulink tool in MATLAB is used to build the block diagram of double-loop neural network system of aiming and stabilization, where the reference model controller is put in the velocity loop and P-regulator is put in the position loop, with feedforward velocity control. Presented the method of synthesis of the neural network reference model controller that is implemented in the Neural Network Toolbox in MATLAB. System tests with the broad range of parameter values determined the key parameters defining the control quality. Optimal values of the key parameters were found to provide the highest control performance. System simulation and analysis of the obtained results is given.References
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Copyright (c) 2015 B. I. Kuznetsov, T. E. Vasilets, O. O. Varfolomiyev
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