Paper:
Substitute Target Learning Based Control System for Control Knowledge Acquisition Within Constrained Environment
Syafiq Fauzi Kamarulzaman, Takeshi Shibuya, and Seiji Yasunobu
Department of Intelligent Interaction Technologies, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
Real-time operations are usually conducted within a constrained environment. A human requires constantly updated knowledge to respond flexibly under different constraints to configure a control method around the constraints. In this research, a control system based on substitute target learning is proposed to enable control operations to configure their own control method around the constraints. This control system is applied to an inverted pendulum control system and its effectiveness is confirmed through a series of simulations and an experiment using a real machine.
- [1] E. Kawana and S. Yasunobu, “An Intelligent Control System Using Object Model by Real-Time Learning,” Proc. of SICE Annual Conf., pp. 2792-2797, 2007.
- [2] R. S. Sutton and A. G. Barto, “Reinforcement Learning An Introduction,” MIT Press, 1998.
- [3] T. Matsubara and S. Yasunobu, “An Intelligent Control Based on Fuzzy Target and Its Application to car like Vehicle,” Proc. of SICE Annual Conf., 2004.
- [4] S. Yasunobu and H. Yamasaki, “Evolutionary Control Method and Swing Up and Stabilization Control of Inverted Pendulum,” Proc. of 9th IFSA World Congress, pp. 2078-2083, 2001.
- [5] V. N. Vichugov, G. P. Tsapko, and S. G. Tsapko, “Application of Reinforcement Learning in Control System Development,” Proc. of The 9th Russian-Korean Int. Symposium on Science and Technology , pp. 732-733, 2005.
- [6] N. Kazuhiro, T. Tsubone, and Y. Wada, “Possibility of reinforcement learning using event-related potential toward an adaptive BCI,” IEEE Conf., pp. 1720-1725, 2009.
- [7] M. Riedmiller, “Neural Reinforcement Learning to swing-up and balance a real pole,” IEEE Conf., pp. 3191-3196, 2005.
- [8] S. Nakamura and S. Hashimoto, “Hybrid Learning Strategy to solve Pendulum Swing-Up Problem for Real Hardware,” IEEE Int. Conf. on Robotics and Biomimetics, pp. 1972-1977, 2007.
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