Mixed H<sub>2</sub>/Sliding Mode Controller Design for Human Swing Leg System

Ali, Hazem I.; Kadhim, Mustafa J.

doi:10.1109/scee.2018.8684215

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Assuming that there is no friction force, the dynamics model of the system can be expressed as general form below is [15].…”

Section: Fig (1a and 1b)mentioning

confidence: 99%

Comparative Between Backstepping and Adaptive Backstepping Control for Controlling Prosthetic Knee

2023

IJCCCE

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The lower limb amputees are increasing day by day. This has led to an increase in research in the field of prosthetic knee. In this work, a prosthetic knee was designed and developed to assist human movements and more quality of life for millions of individuals who have lost lower limbs. The dynamic model and parameter identification of a two degree of freedom (2-DOF) joint prosthetic knee is derived according to the Lagrangian dynamic approach. The two controllers Backstepping and Adaptive Backstepping are adopted to control the system. Stability analysis and controller design dependent on Lyapunov theory are assessed to prove a tracking of a desired trajectory. From the results, found that the quantitative comparison between the two controllers, showed significant improvement in results in position tracking. To comparison between Backstepping control and Adaptive Backstepping control, at the control action consumptions. It was found that the position error of the prosthetic knee in Backstepping control is by 9% at link 1 (thigh) and 7.4% at link 2 (shank) compared with desired trajectory, while in Adaptive Backstepping control is by 1.16% at link 1 and 1.65% at link 2 compared with desired trajectory. When comparing between Backstepping control and Adaptive Backstepping control, the improvement rate was 7.84 at link 1 and 5.75 at link 2 , the proposed Adaptive Backstepping control, it may be concluded, is more robust against this perturbation and to deal with uncertainty. Therefore, the controller is built in a MATLAB environment, and its performance and robustness are assessed. Index Terms— Prosthetic knee, Backstepping control, Adaptive Backstepping control, Lyapunov theory.

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“…Assuming that there is no friction force, the dynamics model of the system can be expressed as general form below is [15].…”

Section: Fig (1a and 1b)mentioning

confidence: 99%

Comparative Between Backstepping and Adaptive Backstepping Control for Controlling Prosthetic Knee

2023

IJCCCE

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“…The inverted pendulum system is a common multi-variable, nonlinear, and naturally unstable system. Its control techniques are widely used in the military, aerospace, robotics, and industrial process areas [12].…”

Section: The Dynamic Model Of the Nonlinear Inverted Pendulum Systemmentioning

confidence: 99%

PID Neural Controller Design for Nonlinear Inverted Pendulum System

2023

IJIES

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The inverted pendulum (IP) system, is a highly coupled, complex, nonlinear system in which the performance of the system is adversely affected by parameter uncertainty and outside disturbances. Therefore, these complications must be managed by the controllers created for such systems. The primary objective of this work is to develop four control structures, including integer order proportional integral derivative neural network controllers for inverted pendulums that deal with trajectory tracking issues. Proportional-integral-derivative neural network structure1 (PIDNNS1), proportional-integral-derivative neural network structure2 (PIDNNS2), proportional-integral-derivative neural network structure3 (PIDNNS3), and proportional-integral-derivative neural network structure4 (PIDNNS4) are the controller structures for inverted pendulum (IP) system . The ant colony optimization (ACO) is a metaheuristic optimization method that is offered to optimize. the controllers' settings while minimizing the cost function. The proposed controllers' resilience to outside disturbances and parameter uncertainty is also tested. The results using MATLAB code demonstrate that the PIDNNS4 controller, which best has a reduced cost function equal to (1.177494), (1.273627), (1.209761) for trajectory tracking, parameters uncertainty, and disturbances rejection for the inverted pendulum (IP) system. and the best controller for stabilization with a low-cost function is the PIDNNS1 controller (1.280839).

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Improving the performance of medical robotic system using H∞ loop shaping robust controller

Ali

Raafat

Al-Khazraji

2020

IJMIC

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Mixed H₂/Sliding Mode Controller Design for Human Swing Leg System

Cited by 3 publications

References 7 publications

Comparative Between Backstepping and Adaptive Backstepping Control for Controlling Prosthetic Knee

Comparative Between Backstepping and Adaptive Backstepping Control for Controlling Prosthetic Knee

PID Neural Controller Design for Nonlinear Inverted Pendulum System

Improving the performance of medical robotic system using H∞ loop shaping robust controller

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Mixed H2/Sliding Mode Controller Design for Human Swing Leg System

Cited by 3 publications

References 7 publications

Comparative Between Backstepping and Adaptive Backstepping Control for Controlling Prosthetic Knee

Comparative Between Backstepping and Adaptive Backstepping Control for Controlling Prosthetic Knee

PID Neural Controller Design for Nonlinear Inverted Pendulum System

Improving the performance of medical robotic system using H∞ loop shaping robust controller

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Product

Resources

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Mixed H₂/Sliding Mode Controller Design for Human Swing Leg System