Robust adaptive control of flexible joint robots
Abstract
During the 1980's, joint stiffness of industrial robots was experimentally observed and described by constant torsional springs. It was concluded that neglecting the joint flexibility in control strategies limits the robot's ability to perform high speed and high precision operations. Robots were introduced into industrial environments to increase production and to lower costs. The need for reprogramming with different loads and tasks wasted valuable time, therefore adaptive instead of fixed control laws were desirable. The desired actuator trajectory in a flexible joint robot is dependent not only on the desired kinematic trajectory of the link but also on the link dynamics. Unfortunately, link dynamic parameters are unknown in most cases, as a result the desired actuator trajectory is also unknown. To overcome this difficulty, a number of control schemes require the feedback of link acceleration and link jerk. In this thesis we describe three control schemes for flexible joint robots which do not use link jerk or acceleration. One of the controllers is suitable for trajectory tracking when the robot parameters are known in advance. The other two control laws are derived from candidate Lyapunov functions which resemble the energy of the arm deviating from the desired trajectory. Trajectory tracking and adaptation of robot arm parameters are possible with two of the controllers described in this thesis. Our control schemes do not require the numerical differentiation of the velocity signal, or the inversion of the inertial matrices.
Degree
Ph.D.
Advisors
Ahmad, Purdue University.
Subject Area
Electrical engineering
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