MODEL-PREDICTIVE IMPEDANCE CONTROL - A MODEL FOR JOINT MOVEMENT

Impedance control has been suggested as the strategy employed by the c entral nervous system to control human postures and movements. A reali zation of this strategy is presented that uses a model predictive cont rol algorithm as a higher motor controller. External disturbances are explicitly included in the model. The combination of 3 key factors-joi nt impedance control, model predictive controller, and external distur bance input-forms the basis for the generality of this model. The mode l was applied to 3 different types of joint movements: a tracking move ment with an unpredicted disturbance, a rhythmic movement, and an unst able biped model of human walking. Computer simulation results showed excellent performance of the model in all 3 cases for optimal values o f active joint impedances and an exact match between the musculoskelet al system and the model internal to the model predictive controller. T he controller was also able to maintain acceptable performance in the presence of a 25% mismatch between the musculoskeletal system and its internal model.