TY - GEN
T1 - Performance characteristics of an improved single neuron PID controller using additional error of an inversed control signal
AU - Putro, Benyamin Kusumo
AU - Rif'An, Muhammad
PY - 2016/2/25
Y1 - 2016/2/25
N2 - A novel single neuron adaptive PID controller system is proposed by utilizing a new quadratic error performance function. In this new quadratic of error performance function, an additional error of thereference control signal between the input of the plant and the inversed of the plant output is added to the conventional input error of the single neuron controller to update the neuron weights in its learning mechanism. To accomplish the new quadratic error function, an inverse neural network is necessary put into the structure of the control system, for providing the inversed plant output as the feedback of the control signal. By using this new quadratic error performance function, the single neuron PID controller system is evaluated and compare with that of the conventional single neuron PID system, in terms of the rise time, the settling time and the overshoot of the system. The simulation results show that the convergence speed of the new adaptive single neuron PID system is increased and the control performance is greatly improve, outperformed the classical single neuron adaptive PID controller, especially in its strong robustness and better self-adaptation.
AB - A novel single neuron adaptive PID controller system is proposed by utilizing a new quadratic error performance function. In this new quadratic of error performance function, an additional error of thereference control signal between the input of the plant and the inversed of the plant output is added to the conventional input error of the single neuron controller to update the neuron weights in its learning mechanism. To accomplish the new quadratic error function, an inverse neural network is necessary put into the structure of the control system, for providing the inversed plant output as the feedback of the control signal. By using this new quadratic error performance function, the single neuron PID controller system is evaluated and compare with that of the conventional single neuron PID system, in terms of the rise time, the settling time and the overshoot of the system. The simulation results show that the convergence speed of the new adaptive single neuron PID system is increased and the control performance is greatly improve, outperformed the classical single neuron adaptive PID controller, especially in its strong robustness and better self-adaptation.
KW - adaptive learning system
KW - backpropagation learning
KW - neural networks controller
KW - PID controller
KW - single neuron PID
UR - http://www.scopus.com/inward/record.url?scp=84971251140&partnerID=8YFLogxK
U2 - 10.1109/WCICSS.2015.7420324
DO - 10.1109/WCICSS.2015.7420324
M3 - Conference contribution
AN - SCOPUS:84971251140
T3 - 2015 World Congress on Industrial Control Systems Security, WCICSS 2015
SP - 58
EP - 62
BT - 2015 World Congress on Industrial Control Systems Security, WCICSS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - World Congress on Industrial Control Systems Security, WCICSS 2015
Y2 - 14 December 2015 through 16 December 2015
ER -