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Configuration space Control.
MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB
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Complicated systems with nonlinear time-varying behavior are difficult to control using classical linear feedback methods applied separately to individual degrees of freedom. At the present, mechanical manipulators, for example, are limited in their rate of movement by the inability of traditional feedback systems to deal with time-varying inertia, torque coupling effects between links and Coriolis forces. Analysis of the dynamics of such systems, however, provides the basic information needed to achieve adequate control. Implementation of a control system based on such analysis is not straightforward, however, since impractical amounts of computation or memory may be called for. We propose a new method that balances the trade-off between computation and storage costs. The actuator torques required to move a manipulator along a trajectory are calculated using coefficients found in a look-up table indexed by the configuration of the manipulator. Feedback plays only an indirect role in correcting for small differences between the state of the actual device and that of a dynamic model.
APPROVED FOR PUBLIC RELEASE