Abstract
This article considers intelligent control for a class of nonholonomic systems using a neurocontroller (NC) and a genetic algorithm (GA). First, we introduce the design of the NC with use of the GA, and then we apply the NC to control two typical examples of nonholonomic systems: a hopping robot in the flight phase and a four-wheel vehicle. In order to verify the effectiveness of the control system, the performance of the NC is investigated and also compared to that of the so-called direct gradient descent control (DGDC) approach, which is able to utilize a GA with the same examples in the comparison. Simulations show that the NC could achieve a competitive performance and control the nonholonomic systems effectively. Furthermore, the use of the NN and GA provide a straightforward solution for the problem without the need of the chained form conversion.
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This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008
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Kinjo, H., Uezato, E., Duong, S.C. et al. Neurocontroller with a genetic algorithm for nonholonomic systems: flying robot and four-wheel vehicle examples. Artif Life Robotics 13, 464–469 (2009). https://doi.org/10.1007/s10015-008-0609-2
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DOI: https://doi.org/10.1007/s10015-008-0609-2