Abstract: High redundancy and strong uncertainty are two main characteristics for underwater robotic manipulators with unlimited workspace and mobility, but they also make the motion planning and control difficult and complex. In order to setup the groundwork for the research on control schemes, the mathematical representation is built by using the Denavit-Hartenberg (D-H) method [9]&[12]; in addition to the geometry of the manipulator which was studied for establishing the direct and inverse kinematics. Then, the dynamic model is developed and used by employing the Lagrange theorem. Furthermore, derivation and computer simulation is accomplished using the MATLAB environment. The result obtained is compared with mechanical system dynamics analysis software, ADAMS. In addition, the creation of intelligent artificial skin using Interlink Force Sensing ResistorTM technology is presented as groundwork for future work
Abstract: This paper describes a practical approach to design
and develop a hybrid learning with acceleration feedback control
(HLC) scheme for input tracking and end-point vibration suppression
of flexible manipulator systems. Initially, a collocated proportionalderivative
(PD) control scheme using hub-angle and hub-velocity
feedback is developed for control of rigid-body motion of the system.
This is then extended to incorporate a further hybrid control scheme
of the collocated PD control and iterative learning control with
acceleration feedback using genetic algorithms (GAs) to optimize the
learning parameters. Experimental results of the response of the
manipulator with the control schemes are presented in the time and
frequency domains. The performance of the HLC is assessed in terms
of input tracking, level of vibration reduction at resonance modes and
robustness with various payloads.