Combining a nonlinear open-loop compensator with a PID feedback controller improves joint angle control in electrically stimulated muscle when the underlying mathematical model is accurate.
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Hybrid nonlinear-PID control may enhance FES accuracy in animal models when model precise; leaves open human translation.
Designs of both open- and closed-loop controllers of electrically stimulated muscle that explicitly depend on a nonlinear mathematical model of muscle input-output properties are presented and evaluated. The muscle model consists of three factors: a muscle activation dynamics factor, an angle-torque relationship factor, and an angular velocity torque relationship factor. These factors are multiplied to relate output torque to input stimulation and joint angle. An experimental method for the determination of the parameters of this model was designed, implemented, and evaluated. An open-loop nonlinear compensator, based upon this model, was tested in an animal model. Its performance in the control of joint angle in the presence of a known load was compared with a PID controller, and with a combination of the PID controller and the nonlinear compensator. The performance of the nonlinear compensator appeared to be strongly dependent on modeling errors. Its performance was roughly equivalent to that of the PID controller alone: somewhat better when the model was accurate, and somewhat worse when it was inaccurate. Combining the nonlinear open loop compensator with the PID feedback controller improved performance when the model was accurate.
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Veltink et al. (1992) studied this question.
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