Application of active force control and iterative learning in a 5-link biped robot
Document Type
Article
Publication Date
1-1-2003
Abstract
This paper investigates the efficacy of the implementation of the conventional Proportional-Derivative (PD) controller and different Active Force Control (AFC) strategies to a 5-link biped robot through a series of simulation studies. The performance of the biped system is evaluated by making the biped walk on a horizontal flat surface, in which the locomotion is constrained within the sagittal plane. Initially, a classical PD controller has been used to control the biped robot. Then, a disturbance elimination method called Active Force Control (AFC) schemes has been incorporated. The effectiveness and robustness of the AFC as �disturbance rejecter� has been examined when a conventional crude approximation (AFCCA), and an intelligent active force control scheme, which is known as Active Force Control and Iterative Learning (AFCAIL) are employed. It is found that for both of the AFC control schemes proposed, the system is robust and stable even under the influence of disturbances. An attractive feature of the AFCAIL scheme is that inertia matrix tuning becomes much easier and automatic without any degradation in the performance.
Keywords
Biped, proportional-derivative control, active force control, crude approximation, iterative learning
Divisions
ai
Publication Title
Journal of Intelligent & Robotic Systems
Volume
37
Issue
2