Manas C. Menon

Design of a semi-passive heavy-duty mobile robotic system for automated assembly inside an aircraft body

We present an initial design of a mobile robotic system for automated assembly inside an aircraft body. This system allows for the positioning control of a heavy duty end effector that is working on the far side of a thin wall at any orientation. It utilizes electromagnets to hold the end effector against the wall, as well as linear motor type actuation for locomotion. Initial testing on a prototype verifies the effectiveness of some of the chosen design parameters.

Iterative learning control of shape memory alloy actuators with thermoelectric temperature regulation for a multifunctional car seat

Modeling and control of a thermo-mechanical system consisting of Peltier-effect thermoelectric devices (TED) and shape memory alloy (SMA) actuators are presented. Bi-layer TEDs sandwiching SMA actuators can generate motion at the SMA wires and simultaneously regulate the temperature of contacting surfaces. The system is applied to an advanced car seat for rapid heating and cooling as well as for massaging of the driver. First, the design of the thermo-mechanical system is described, followed by the modeling of thermal and mechanical behavior of the system. An iterative learning control (ILC) is applied to the control of multi-axis SMA actuators for generating periodic waves for massaging. In addition to the motion control the temperature of the car seat surface is regulated to provide the driver with thermal comfort

Design and Control of Paired Mobile Robots Working Across a Thin Plate With Application to Aircraft Manufacturing

A pair of mobile robots acting on opposite sides of a thin plate is developed for a class of tasks where robots have to work together, carrying a pair of end-effectors and traversing across a plate surface. Using powerful magnets, the paired robots attract each other, support themselves against gravity, and generate traction force to move across the panel. First, the design concept of paired mobile robots is presented, followed by dynamic modeling and magnetic analysis. Conditions for preventing the robot from falling as well as from slipping on the plate surface are examined. Time-optimal control of the paired robots subject to the no-fall, no-slip conditions is formulated and solved numerically. Precision positioning control using a laser beacon is designed and tested. A prototype of the paired robots using Halbach array permanent magnets and Lorentz force actuators is developed, and the control methods are implemented and tested on the prototype.

Neighbor Learning Control: Learning Control for Multiple Subsystems

With the rise of smart material actuators, it has become possible to design and build systems with a large number of small actuators. Many of these actuators exhibit a host of nonlinearities including hysteresis. Learning control algorithms can be used to guarantee good convergence of these systems even in the presence of the nonlinearities. However, they have a difficult time dealing with certain classes of noise or disturbances. We present a neighbor learning algorithm to control systems of this type with multiple identical actuators. In addition, we present a neighbor learning algorithm to control these systems for a certain class of non-identical actuators. We prove that in certain situations these algorithms provide improved convergence when compared to traditional iterative learning control techniques. Simulations results are presented that corroborate our expectations from the proofs.© 2007 ASME