Abstract
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.
Similar content being viewed by others
References
Thathachar MAL (2002) Varieties of learning automata: an overview. IEEE Trans Systems, Men and Cybernetics-Part B: Cybernetics 32(6):711–722
Hara M, Abe K (1997) Decentralized learning control of markov decision processes. IEICE D-2 J80-D-2(1):363–366
Mogami Y, Baba N (1991) Variable hierarchical structure learning automata operating in a non-stationary multiteacher environment. T IEE Jpn, D-2 J74-D-I(7):401–408
Zeng X, Zhou J, Vasseur C (2000) A strategy for controlling nonlinear systems using learning automaton. Automatica 36: 1517–1524
Author information
Authors and Affiliations
Corresponding author
Additional information
This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008
About this article
Cite this article
Sawada, H., Shin, JS., Shoji, F. et al. Learning type PID control system using input dependence reinforcement scheme. Artif Life Robotics 13, 139–143 (2008). https://doi.org/10.1007/s10015-008-0573-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10015-008-0573-x