Control and Learning by the State Space Model: Experimental Findings

Abstract

This is the second of a two part presentation of a model for motor control and learning. The model was implemented using a small computer and the MIT -Scheinman manipulator. Experiments were conducted which demonstrate the controller's ability to learn new movements, adapt to mechanical changes caused by inertial and elastic loading, and generalize its behavior among similar movements. A second generation model, based on improvements suggested by these experiments is suggested.