Flexible multibody dynamics and intelligent control of a hydraulically driven hybrid redundant robot machine

Abstract

The assembly and maintenance of the International Thermonuclear Experimental
\nReactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by
\nthe robot involve welding, material handling, and machine cutting from inside the VV.
\nThe VV is made of stainless steel, which has poor machinability and tends to work
\nharden very rapidly, and all the machining operations need to be carried out from inside
\nof the ITER VV. A general industrial robot cannot be used due to its poor stiffness in
\nthe heavy duty machining process, and this will cause many problems, such as poor
\nsurface quality, tool damage, low accuracy. Therefore, one of the most suitable options
\nshould be a light weight mobile robot which is able to move around inside of the VV
\nand perform different machining tasks by replacing different cutting tools.
\nReducing the mass of the robot manipulators offers many advantages: reduced material
\ncosts, reduced power consumption, the possibility of using smaller actuators, and a
\nhigher payload-to-robot weight ratio. Offsetting these advantages, the lighter weight
\nrobot is more flexible, which makes it more difficult to control. To achieve good
\nmachining surface quality, the tracking of the end effector must be accurate, and an
\naccurate model for a more flexible robot must be constructed.
\nThis thesis studies the dynamics and control of a 10 degree-of-freedom (DOF)
\nredundant hybrid robot (4-DOF serial mechanism and 6-DOF 6-UPS hexapod parallel
\nmechanisms) hydraulically driven with flexible rods under the influence of machining
\nforces. Firstly, the flexibility of the bodies is described using the floating frame of
\nreference method (FFRF). A finite element model (FEM) provided the Craig-Bampton
\n(CB) modes needed for the FFRF. A dynamic model of the system of six closed loop
\nmechanisms was assembled using the constrained Lagrange equations and the Lagrange
\nmultiplier method. Subsequently, the reaction forces between the parallel and serial
\nparts were used to study the dynamics of the serial robot. A PID control based on
\nposition predictions was implemented independently to control the hydraulic cylinders
\nof the robot.
\nSecondly, in machining, to achieve greater end effector trajectory tracking accuracy for
\nsurface quality, a robust control of the actuators for the flexible link has to be deduced.
\nThis thesis investigates the intelligent control of a hydraulically driven parallel robot
\npart based on the dynamic model and two schemes of intelligent control for a hydraulically driven parallel mechanism based on the dynamic model: (1) a fuzzy-PID
\nself-tuning controller composed of the conventional PID control and with fuzzy logic,
\nand (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self-tuning of the
\ngains of the PID controller, which are implemented independently to control each
\nhydraulic cylinder of the parallel mechanism based on rod length predictions. The serial
\ncomponent of the hybrid robot can be analyzed using the equilibrium of reaction forces
\nat the universal joint connections of the hexa-element. To achieve precise positional
\ncontrol of the end effector for maximum precision machining, the hydraulic cylinder
\nshould be controlled to hold the hexa-element.
\nThirdly, a finite element approach of multibody systems using the Special Euclidean
\ngroup SE(3) framework is presented for a parallel mechanism with flexible piston rods
\nunder the influence of machining forces. The flexibility of the bodies is described using
\nthe nonlinear interpolation method with an exponential map. The equations of motion
\ntake the form of a differential algebraic equation on a Lie group, which is solved using a
\nLie group time integration scheme. The method relies on the local