TY - GEN
T1 - Learning type PID control system using input dependence reinforcement scheme
AU - Sawada, Hideharu
AU - Shin, Ji Sun
AU - Shoji, Fumihiro
AU - Lee, Hee Hyol
PY - 2008
Y1 - 2008
N2 - PID control has widely used in the field of process control and a lot of methods have been used to design PID parameters. When the characteristic values of a controlled object are changed due to a change over the years or disturbance, the skilled operators observe the feature of the controlled responses and adjust the PID parameters using their knowledge and know-how, and a lot of labors are required to do it. In this research, we design a learning type PID control system using the stochastic automaton with learning function, namely learning automaton, which can autonomously adjust the control parameters updating the state transition probability using relative amount of controlled error. We show the effectiveness of the proposed learning type PID control system by simulations.
AB - PID control has widely used in the field of process control and a lot of methods have been used to design PID parameters. When the characteristic values of a controlled object are changed due to a change over the years or disturbance, the skilled operators observe the feature of the controlled responses and adjust the PID parameters using their knowledge and know-how, and a lot of labors are required to do it. In this research, we design a learning type PID control system using the stochastic automaton with learning function, namely learning automaton, which can autonomously adjust the control parameters updating the state transition probability using relative amount of controlled error. We show the effectiveness of the proposed learning type PID control system by simulations.
KW - Learning automaton
KW - Learning control
KW - PID control
KW - State transition probability
UR - http://www.scopus.com/inward/record.url?scp=78449254004&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78449254004&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:78449254004
SN - 9784990288020
T3 - Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08
SP - 389
EP - 392
BT - Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08
T2 - 13th International Symposium on Artificial Life and Robotics, AROB 13th'08
Y2 - 31 January 2008 through 2 February 2008
ER -