Abstract
Knowledge-based methods gain increasing importance in automation systems. But many real applications are too complex or there is too little understanding to acquire useful knowledge. Therefore machine learning techniques like the directed self-learning which is used here may help to bridge this gap. In order to point out the advantages of machine learning in process automation, we applied the directed self-learning method to the control of an inverted pendulum. Through a comparison between a knowledge-based and a machine learning version of the controller, both based on the knowledge of the same expert, results were achieved which demonstrate the usefulness of machine learning in control applications.
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Brockmann, W.: Combining Real-Time with Knowledge Processing Techniques. 5th Int. Conf. on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA-AIE, Springer Verlag, Berlin, 1992, 594–603
Brockmann, W.: Online Machine Learning for Adaptive Control. IEEE Int. Workshop on Emerging Technologies and Factory Automation ETFA, CRL Publishing Ltd., London, 1992, 190–195
Mandic, N.J., Scharf, E.M. et. al.: Practical Application of a Heuristic Fuzzy Rule-Based Controller to the Dynamic Control of a Robot Arm. IEE Proc., Vol. 132, Pt D, No. 4, 1985
Shao, S.: Fuzzy Self-Organizing Controller and its Application for Dynamic Processes. Fuzzy Sets and Systems, 26(1998), 151–164
Slender, J.: SOL — Second Order Learning. Brainware GmbH, Berlin, 1990
Yamakawa, T.: Stabilization of an Inverted Pendulum by a High-Speed Fuzzy Logic Controller Hardware System. Fuzzy Sets and Systems 32(1989), 161–180
Zhang, B., Grant, E.: Experiments in Adaptive Rule-Based Control. 3rd Int. Conf. on Industrial and Engineering Appl. of Art. Int. and Expert Systems, 1990, 563–568
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© 1994 Springer-Verlag Berlin Heidelberg
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Brockmann, W. (1994). On the role of machine learning in knowledge-based control. In: Bergadano, F., De Raedt, L. (eds) Machine Learning: ECML-94. ECML 1994. Lecture Notes in Computer Science, vol 784. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57868-4_69
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DOI: https://doi.org/10.1007/3-540-57868-4_69
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