Differential Flatness Theory and Industrial Robotics

Abstract

This chapter analyzes the use of nonlinear control and filtering methods to the solution of industrial robotics problems, such as the adaptive control of MIMO robotic manipulators without prior knowledge of the robot’s dynamical model, adaptive control of underactuated robotic manipulators, that is robots having less actuators than their degrees of freedom, observer-based adaptive control of MIMO robotic manipulators in which uncertainty is not related only to the unknown dynamic model of the robot but also comes from the inability to measure all elements of the robot’s state vector, and Kalman Filter-based control of MIMO robotic manipulators. Finally, differential flatness theory is proposed for developing a control scheme over a communication network that is characterized by transmission delays or losses in the transmitted information.