Abstract

Biological systems are highly nonlinear, have at least one pair of muscles actuating every degree of freedom at any joint, and possess neural transmission delays in their feedforward (efferent) and feedback (afferent) paths. The modeling and control of such systems for nominally small trajectories, such that linear analysis applies, is the subject of this article. In these systems, coactivation of pairs of muscles for every degree of freedom stabilizes the system: therefore the open loop system is stable. The purpose of feedback is to decouple the links, coordinate the movement of the linkages, execute tasks under relatively large delays, and control the pole positions. Robustness and insensitivity to disturbance are other attributes of feedback that are also considered in this article. Robots of the future may have similar delays in their feedback and feedforward paths. The robotic delays are primarily computational, and have two major sources. The first source is computational delays brought about by better vision and tactile systems in the robot and the integration of all sensory modalities. The second source of delays is due to computations needed for indirect measurements of desired physical attributes and quantities. The main results of this paper, therefore, can be extended to robots whose capabilities extend beyond the robots of today, and are capable of more sophisticated tasks including communication and collaboration with humans. © 2000 John Wiley & Sons, Inc.

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