Adaptive fuzzy control of satellite attitude by reinforcement learning

Autor: Robert Babuska, W. M. Van Buijtenen, G. Schram, H.B. Verbruggen
Rok vydání: 1998
Předmět:
Zdroj: IEEE Transactions on Fuzzy Systems, 6 (2)
ISSN: 1063-6706
DOI: 10.1109/91.669012
Popis: The attitude control of a satellite is often characterized by a limit cycle, caused by measurement inaccuracies and noise in the sensor output. In order to reduce the limit cycle, a nonlinear fuzzy controller was applied. The controller was tuned by means of reinforcement learning without using any model of the sensors or the satellite. The reinforcement signal is computed as a fuzzy performance measure using a noncompensatory aggregation of two control subgoals. Convergence of the reinforcement learning scheme is improved by computing the temporal difference error over several time steps and adapting the critic and the controller at a lower sampling rate. The results show that an adaptive fuzzy controller can better cope with the sensor noise and nonlinearities than a standard linear controller.
Databáze: OpenAIRE