Authors present modular development of an Automatic Microassembly Workcell. Its hardware consists of MM3A R nanomanipulator, PI R linear micromotion stage, Microscope, CCD and VGA cameras. All these components are integrated together and controlled from a single MATLAB R program. In MATLAB R , vision based integrated routines are developed for online tracking and automatic control of the nanomanipulator's orientation, tip position, tip focusing and collision avoidance to assist automation of microassembly procedure. Integration of multiple visual sensors for macro and micro vision allows switching sensing modes based on tasks to be performed for optimal speed and repeatability. Experiments conducted on MM3A R nanomanipulator using developed automation routing show ten times reduction in setup and run time for fundamental micromanipulation tasks such as orientation change, tip positioning, and tip focusing etc. as compared to their manual operation. Safety measures for collision avoidance have also been implemented.
A superscalar microcontroller based system is used to control the Physik Instrumente (PI) piezo-electricultrasonic nano-positioning (PUN) stage for a micro-factory has been proposed by the author. A Linuxbased development board i.e. BeagleBone containing TI AM3358/9 SoC based on an ARM Cortex-A8processor core, is suggested to provide visual servo control to the nano-positioning stage. The stages aredriven at the tuning parameters which have been identified, tested and validated for robustness underuncertainties. The microcontroller i.e. LPC2478 provides the user with the choices of operations on the3.2” QVGA LCD screen and the choice can be made by a 5-key joystick. The PUN stage moves in differentgeometrical patterns as chosen by the user. The stage is placed in the workspace of a femto-second laser.Different patterns are made on the material in question. A camera interfaced to the BeagleBone traces themovements of the nano-positioning stage with the help of image processing routines which can becommunicated to enable further control of actions .As compared to the previous works in this area, the useris given the power for position control, real time tracking, and trajectory planning of the actuator. The userinterface has been made very easy to comprehend. The repeatability of tasks, portability of the assembly,the reduction in the size of the system, power con-sumption and the human involvement are the majorachievements after the inclusion of an embedded platform.1. INTRODUCTIO
Ahstract-The role played by nano positioning stages in Micromanufacturing requires them to be robust to uncertain variations in loading conditions and trajectory generation. The author has previously worked on devising a method for model identification of a precise linear standing wave ultrasonic motor driven nano positioning stage of resolution 100nm. In this paper, the author stresses on designing robust controllers for the estimated models using the principles of internal model control and robust response time. These controllers show a marked improvement of approximately 80% better response from the factory setting controller in terms of rise time and settling time. Their robustness is demonstrated through repetitive experiments of loading and unloading in increments using weights in the range of 2 grams to 50 grams. The effects of changes in velocities from 100mmls to 800mmls are also exhibited. Under uncertainty the designed controller gives an effective response showing same level of overshoot as the positioning stage in recommended conditions and a change of 0.1 to 0.3 milliseconds in the rise and settling time. Model Identification and controller design has been achieved in MATLAB ® . Experimental demonstration of robustness is carried out using PILine ® M663 stage and PIMikroMove ® software.
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