Robust Adaptive Neural Network Control for Wheeled Inverted Pendulum with Input Saturation
- 3.3k Downloads
In this paper, a novel control design is proposed for wheeled inverted pendulum with input saturation. Based on Lyapunov synthesis method, backstepping design procedure and the Neural network (NN) approximation to the uncertainty of the system, the adaptive NN tracking controller is constructed by considering actuator saturation constraints. The stability analysis subject to the effect of input saturation constrains are conducted with the help of an auxiliary design system. The proposed controller guarantees uniformly ultimately bounded of all the signals in the closed-loop system, while the tracking error can be made arbitrarily small. Simulation studies are given to illustrate the effectiveness and the performance of the proposed scheme.
Keywordswheeled inverted pendulum backstepping design neural network (NN) input saturation
Unable to display preview. Download preview PDF.
- 15.Wei, E.P., Li, T.S., Li, J.F., Hu, Y.C.: Neural Network-Based Adaptive Dynamic Surface Control for Inverted Pendulum System. In: The IEEE First International Conference on Cognitive Systems and Information Processing, CSIP 2012, pp. 56–63 (2012)Google Scholar
- 16.Chen, M., Ge, S.S., Choo, Y.: Neural network tracking control of ocean surface vessels with input saturation. In: Proc. of the 2009 IEEE International Conference on Automation and Logistics, ICAL 2009, pp. 85–89 (2009)Google Scholar