Abstract
A proposal for the knee position control design of paraplegic patients with functional electrical stimulation (FES) using control systems and considering norm-bounded uncertainties is presented. A state-space representation of the knee joint model of the paraplegic patient with its nonlinearity is also demonstrated. The use of linear matrix inequalities (LMIs) in control systems with norm-bounded uncertainties for asymptotic stability is analyzed. The model was simulated in the Matlab environment. The matrixKof state space feedback was obtained through LMIs.
Highlights
The application of electrical stimulation in a person’s muscle, more in his motor neurons, causes involuntary contraction of this muscle [1].In order to obtain a muscle contraction it is necessary that the amplitude and duration of the electrical stimulus are inside specific bounds
This paper presents a proposal for the leg position control design of paraplegic patients with functional electrical stimulation (FES) using control systems with uncertainties bounded in norm and a feedback signal obtained from an electrogoniometer which is the most commonly used sensor for measuring the knee joint angle
The graphic of active torque produced by the electric stimulus shows that the curve stabilizes at the mark of 4.6 (N ⋅ m) at 3.1 (s)
Summary
The application of electrical stimulation in a person’s muscle, more in his motor neurons, causes involuntary contraction of this muscle [1]. The degree of muscle activation, α, is a nonlinear function It depends on the duration of the stimulus, d [3]. One serious problem when using FES is that artificially activated muscles fatigue at a faster rate than those activated by the natural physiological processes Due to these problems, a considerable effort has been directed toward developing FES systems based on closed loop control. This paper presents a proposal for the leg position control design of paraplegic patients with FES using control systems with uncertainties bounded in norm and a feedback signal obtained from an electrogoniometer which is the most commonly used sensor for measuring the knee joint angle. As mentioned in [9] “Complex control systems have been recently employed to control the communications among computers, controllers, and sensors due to the enlarging scale of control systems in nowadays applications.” Nowadays, it is a very important issue for dynamic systems design
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