2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE) 2019
DOI: 10.1109/ccece.2019.8861754
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Control of a Mechanical Knee Based on Predictive Control Techniques

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Cited by 2 publications
(4 citation statements)
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“…These characteristics make the finite state machine method fit the environment and cannot adjust the parameters for different sports and users, resulting in low adaptability (Zuo et al, 2021). Campos et al (2019) applied a predictive control technique to perform the control of the knee prosthesis MR proposed by Andrade et al (2018). The authors noticed that the response of the predictive control system presents a minor error in the output compared to the works that use the PI control system.…”
Section: Kneementioning
confidence: 99%
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“…These characteristics make the finite state machine method fit the environment and cannot adjust the parameters for different sports and users, resulting in low adaptability (Zuo et al, 2021). Campos et al (2019) applied a predictive control technique to perform the control of the knee prosthesis MR proposed by Andrade et al (2018). The authors noticed that the response of the predictive control system presents a minor error in the output compared to the works that use the PI control system.…”
Section: Kneementioning
confidence: 99%
“…The authors noticed that the response of the predictive control system presents a minor error in the output compared to the works that use the PI control system. Furthermore, the behavior of the gait cycle with the use of predictive control in prostheses tends to be closer to the gait of a healthy person since the human body operates in its actions anticipatory (Campos et al, 2019). Nordin et al (2018) implemented an adaptive controller to make the damper of a transtibial prosthesis perform well at various frequencies.…”
Section: Kneementioning
confidence: 99%
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“…Content may change prior to final publication. Powered below-Knee prosthesis Finite-state control Natural movement and adaptable [86] Powered ankle-foot prosthesis Finite state controllers High mechanical power and torque [87] Powered prosthetic intervention Finite-state impedance control Enhanced awareness, stability, & power [88] Knee and ankle control Impedance control Reduced clinical challenges [89] Virtual prosthetic leg Feedback linearization Biomimetic and robust [90] Transfemoral prosthesis Least square approach Estimation of knee impedance [91] Transitions b/w ground and ramps Fuzzy logic control Effective control scheme [92] Mechanical knee Predictive control Better approximation of human gait [93] Dynamic swing phase model Langrange dynamic analysis Input compensation for better accuracy [94] Powered lower limb prosthesis Adaptive dynamic programming Testing of 300 gait cycles contraction and expansion to capture the body movement in the real world. The table summarizes the objectives, the role of EMG sensors, and the key outcomes for the articles included.…”
Section: ) Emg Based Work For Lower Limb Prosthesismentioning
confidence: 99%