Neurocontroller Via Adaptive Learning Rates for Stable Path Tracking of Mobile Robots
In this paper, we present a neurocontroller via adaptive learning rates (ALRs) for stable path tracking of mobile robots. The self recurrent wavelet neural networks (SRWNNs) are employed as two neurocontrollers for the control of the mobile robot. Since the SRWNN combines the advantages such as the multi-resolution of the wavelet neural network and the information storage of the recurrent neural network, it can easily cope with the unexpected change of the system. Specially, the ALR algorithm in the gradient-descent method is extended for the multi-input multi-output system and is applied to train the parameters of the SRWNN controllers. The ALRs are derived from the discrete Lyapunov stability theorem, which are used to guarantee the stable path tracking of mobile robots. Finally, through computer simulations, we demonstrate the effectiveness and stability of the proposed controller.
KeywordsMobile Robot Learning Rate Mother Wavelet Reference Trajectory Wavelet Neural Network
Unable to display preview. Download preview PDF.
- 2.Hu, T., Yang, S.X., Wang, F., Mittal, G.S.: A neural network controller for a nonholonomic mobile robot with unknown robot parameters. In: Proc. of the IEEE Int. Conf. Robotics and Automation, pp. 3540–3545 (2002)Google Scholar
- 4.Sousa, C.D., Hemerly, E.M., Galvão, R.K.H.: Adaptive control for mobile robot using wavelet networks. IEEE Trans. Systems, Man, and Cybernetics 32, 493–504 (2002)Google Scholar
- 7.Yoo, S.J., Choi, Y.H., Park, J.B.: Stable predictive control of chaotic systems using self-recurrent wavelet neural network. Int. Jour. Control, Automation and Systems 3, 43–55 (2005)Google Scholar
- 11.Wang, C.M.: Location estimation and uncertainty analysis for mobile robots. In: Proc. of the IEEE Int. Conf. Robotics and Automation, pp. 1230–1235 (1988)Google Scholar
- 12.Haesloop, D., Holt, B.R.: A neural network structure for system identification. In: Proc. of the American Control Conference, pp. 2460–2465 (1990)Google Scholar