Title :
An advanced tracking controller with neural networks for servo systems
Author :
Boyagoda, P.B. ; Nakaoka, M.
Author_Institution :
Graduate Sch. of Sci. & Eng., Yamaguchi Univ., Ube, Japan
fDate :
2/1/2000 12:00:00 AM
Abstract :
A novel controller for generic servo systems using a neural network input-output measurement classifier and a staggered proportional plus integral plus derivative-like gain control scheme is proposed. The controller incorporates a knowledge-based control strategy and does not require a priori knowledge of the plant. The system controller is robust to both structured and unstructured uncertainties
Keywords :
control system analysis; control system synthesis; gain control; neurocontrollers; robust control; servomechanisms; three-term control; control design; control simulation; generic servo systems; knowledge-based control strategy; neural network input-output measurement classifier; robustness; staggered PID-like gain control scheme; structured uncertainties; unstructured uncertainties; Control nonlinearities; Control systems; DC motors; Electric variables control; Mathematical model; Neural networks; Servomechanisms; Sliding mode control; Steady-state; Uncertainty;
Journal_Title :
Industrial Electronics, IEEE Transactions on
