In this paper multilayer neural networks are used to control the balancing of a base-excited inverted pendulum. The pendulum has two degrees of rotational freedom and the base-point moves freely in the three-dimension...
详细信息
ISBN:
(纸本)0780372034
In this paper multilayer neural networks are used to control the balancing of a base-excited inverted pendulum. The pendulum has two degrees of rotational 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 prescribed orientation in spite of disturbing base-point movement. The inclusion of the base-point motion leads to a non-autonomous dynamic system with time-varying parametric excitation, which makes the design of the controller challenging. A control algorithm is proposed that utilizes a set of neural networks to compensate for the effect of system's nonlinearities. These networks are updated on-line. Furthermore, since the pendulum's base-point movement is considered unmeasurable, a novel neuralinverse model is employed to estimate it from measurable variables. The performance of the proposed neural controller has been compared with the performance of the recently developed control law on the same problem. It is shown that the proposed neural controller produces fast, yet well maintained damped responses with reasonable control torques and without a knowledge of the model or model parameters. Additionally, the developed controller does not require measurement of the base-point accelerations, which are difficult to obtain in practice. The work presented here benefits practical problems such as the study of stable locomotion of human upper body and bipedal locomotion.
暂无评论