Output Feedback Direct Adaptive Control for a Two-Link Flexible Robot Subject to Parameter Changes

Abstract

Robots today have an ever growing niche. Many of today's robots are required to perform tasks which demand high level of accuracy in end effector positioning. The links of the robot connecting the joints are large, rigid, and heavy. These manipulators are designed with links, which are sufficiently stiff for structural deflection to be negligible during normal operation. Also, heavy links utilize much of the joint motor's power moving the link and holding them against gravity. Moreover the payloads have to be kept small compared to the mass of the robot itself, since large payloads induce sagging and vibration in the links, eventually bringing about uncertainty in the end effector position. In an attempt to solve these problems lightweight and flexible robots have been developed. These lightweight mechanical structures are expected to improve performance of the robot manipulators with typically low payload to arm weight ratio. The ultimate goal of such robotic designs is to accurate tip position control in spite of the flexibility in a reasonable amount of time. Unlike industrial robots, these robot links will be utilized for specific purposes like in a space shuttle arm. These flexible robots have an increased payload capacity, lesser energy consumption, cheaper construction, faster movements, and longer reach. However, link flexibility causes significant technical problems. The weight reduction leads the manipulator to become more flexible and more difficult to control accurately. The manipulator being a distributed parameter system, it is highly non-linear in nature. Control algorithms will be required to compensate for both the vibrations and static deflections that result from the flexibility. This provides a challenge to design control techniques that: a) gives precise control of desired parameters of the system in desired time, b) cope up with sudden changes in the bounded system parameters, c) gives control on unmodeled dynamics in the form of perturbations, and d) robust performance. Conventional control system design is generally a trial and error process which is often not capable of controlling a process, which varies significantly during operation. Thus, the quest for robust and precise control led researchers to derive various control theories. Adaptive control is one of these research fields that is emerging as timely and important class of controller design. Area much argued about adaptive control is its simplicity and ease of www.intechopen.com