Control of smart exercise machines-part II: Self-optimizing control

  • Li P
  • Horowitz R
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For pt. I see ibid. p. 237-47 (1997). Concerns the design of an
intelligent controller for a class of exercise machines. The control
objective is to cause the user to exercise in a manner that optimizes a
criterion related to the user's mechanical power. The optimal exercise
strategy is determined by an a priori unknown biomechanical behavior,
called the Hill surface, of the individual user. Consequently, the
control scheme must simultaneously: 1) identify the user's biomechanical
behavior; 2) optimize the controller; and 3) stabilize the system to the
estimated optimal states. We address the self-optimization problem in
which both the determination and the eventual execution of the optimal
exercise strategy are accomplished, when the user's biomechanical
behavior is unknown. This is achieved by a combination of an adaptive
controller and a reference generator. The latter switches the desired
exercise strategy between a training strategy and the estimated optimal
strategy. Depending on the switching scheme chosen, it is shown that,
asymptotically, the user will either execute the optimal exercise with
probability one or operate close to it. Experimental results of the
overall system verify the efficacy of the design

Author-supplied keywords

  • Adaptive control
  • Biomechanics
  • Hybrid systems
  • Intelligent control
  • Passivity
  • Robotics
  • Self optimization
  • Velocity field control

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