Patrick J. Schimoler

PhD Dissertation Defense

Mechanical Engineering Graduate Program
 

Title:

Iterative Learning Control of an Elbow Joint Motion Simulator

ABSTRACT:

Orthopaedic research studies the function, injury, and repair of the musculoskeletal system and often employs cadaveric testing.  The use of body donations admits investigation into passive tissue behavior that is impossible in vivo, but all cadaveric investigations into movements necessarily lack the trained nervous system to actuate movement. The joint motion simulator is an orthopaedic testbed developed to provide repeatable actuation of a cadaveric specimen. The control of joint motion simulators is complicated by nonlinearities, tendon actuation, and specimen variation. 

This dissertation develops a control system for an elbow joint motion simulator. A combination of decoupling, mixed sensitivity robust control, and iterative learning control are used to track sinusoidal flexion/extension and pronation/supination motions both individually and simultaneously. Small muscle co-contractions are maintained to prevent tendon slack. The control approach is applied to three systems of increasing complexity: flexion/extension controlled by the brachialis, flexion/extension controlled by the brachialis and triceps, and both flexion/extension and pronation/supination controlled by the biceps, brachialis, pronator, and triceps. All three levels of control are applied to a mechanical elbow and the two kinematic degree of freedom control is also applied to both a large and small cadaveric elbow.

This dissertation establishes a structured method of control synthesis for joint motion simulators devoid of the ad hoc methods often employed in joint motion simulator control.