On control of a base-excited inverted pendulum using neural networks

In this paper a neural-network-based control technique is proposed for stab ilizing a base-excited inverted pendulum. The pendulum has two degrees of r otational freedom and the base-point moves freely in the three-dimensional space. The goal is to apply control torques to keep the pendulum in a presc ribed position in spite of disturbing base-point movements. First, the prob lem of modeling such a highly nonlinear, non-autonomous system with neural networks is investigated. The model is then applied within a feedback contr ol loop to keep the pendulum about the upright position. The stability of t he control system in the presence of the approximation errors of neural net works is also analyzed. The examination of the proposed controller, through simulations, demonstrates the promise of the methodology and exhibits posi tive aspects, which cannot be achieved by the previously developed techniqu es, based on Lyapunov stability analysis. These aspects include fast, yet w ell-maintained damped responses with smooth control torques. The work prese nted here, can benefit practical problems such as the study of stable locom otion of human upper body and bipedal robots. (C) 2000 The Franklin Institu te. Published by Elsevier Science Ltd. All rights reserved.