Neural Network Control of a Rehabilitation Robot by State and Output Feedback
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In this paper, neural network control is presented for a rehabilitation robot with unknown system dynamics. To deal with the system uncertainties and improve the system robustness, adaptive neural networks are used to approximate the unknown model of the robot and adapt interactions between the robot and the patient. Both full state feedback control and output feedback control are considered in this paper. With the proposed control, uniform ultimate boundedness of the closed loop system is achieved in the context of Lyapunov’s stability theory and its associated techniques. The state of the system is proven to converge to a small neighborhood of zero by appropriately choosing design parameters. Extensive simulations for a rehabilitation robot with constraints are carried out to illustrate the effectiveness of the proposed control.
KeywordsAdaptive neural network control Full state feedback control Lyapunov’s direct method Output feedback control Rehabilitation robot
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- 5.He, W., Ge, S.S., Li, Y., Chew, E., Ng, Y.S.: Impedance control of a rehabilitation robot for interactive training, In Proceedings of the 2012 International Conference on Social Robotics, Chengdu, China, pp. 526–535 (2012)Google Scholar
- 15.Ge, S.S., Lee, T.H., Harris, C.J.: Adaptive Neural Network Control of Robotic Manipulators. London, UK: World Scientific (1998)Google Scholar
- 16.Lewis, F.L., Jagannathan, S., Yeildirek, A.: Neural network control of robot manipulators and nonlinear systems. Taylor & Francis, London (1999)Google Scholar
- 17.Wang, C., Hill, D.J.: Deterministic learning theory for identification, recognition, and control. CRC Press (2009)Google Scholar
- 28.He, W., Ge, S.S., How, B.V.E., Choo, Y.S.: Dynamics and Control of Mechanical Systems in Offshore Engineering (2014)Google Scholar
- 34.Ge, S.S., Hang, C.C., Lee, T.H., Zhang, T.: Stable Adaptive Neural Network Control. Kluwer Academic, Boston, USA (2001)Google Scholar
- 37.He, W., Ge, S.S.: Robust adaptive boundary control of a vibrating string under unknown time-varying disturbance. IEEE Trans. Control Syst. Technol. 20(1), 48–58 (2012)Google Scholar
- 42.Khalil, H.K., Systems Nonlinear. Prentice Hall, New Jersey USA (2002)Google Scholar