IEEE transactions on control systems technology, 2009-01, Vol.17 (1), p.207-214
2009
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Details
- Autor(en) / Beteiligte
- Titel
- Adaptive Neural Sliding Mode Control of Nonholonomic Wheeled Mobile Robots With Model Uncertainty
- Ist Teil von
- IEEE transactions on control systems technology, 2009-01, Vol.17 (1), p.207-214
- Ort / Verlag
- New York, NY: IEEE
- Erscheinungsjahr
- 2009
- Quelle
- IEEE Xplore
- Beschreibungen/Notizen
- This brief proposes an adaptive neural sliding mode control method for trajectory tracking of nonholonomic wheeled mobile robots with model uncertainties and external disturbances. The dynamic model with model uncertainties and the kinematic model represented by polar coordinates are considered to design a robust control system. Self recurrent wavelet neural networks (SRWNNs) are used for approximating arbitrary model uncertainties and external disturbances in dynamics of the mobile robot. From the Lyapunov stability theory, we derive online tuning algorithms for all weights of SRWNNs and prove that all signals of a closed-loop system are uniformly ultimately bounded. Finally, we perform computer simulations to demonstrate the robustness and performance of the proposed control system.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 1063-6536eISSN: 1558-0865DOI: 10.1109/TCST.2008.922584Titel-ID: cdi_pascalfrancis_primary_21051336
- Format
- –
- Schlagworte
- Adaptative systems, Adaptive control, Adaptive sliding mode control (ASMC), Applied sciences, Computer science, control theory, systems, Computer simulation, Control system synthesis, Control systems, Control theory. Systems, Disturbances, Dynamical systems, Dynamics, Exact sciences and technology, Kinematics, Mobile robots, model uncertainty, Neural networks, polar coordinates, Programmable control, Recurrent neural networks, Robotics, Robots, Robust control, self recurrent wavelet neural networks (SRWNNs), Sliding mode control, Trajectory, Uncertainty