Abstract
Active prosthetic knees (APKs) are widely used in the past decades. However, it is still challenging to make them more natural and controllable because: (1) most existing APKs that use rigid actuators have difficulty obtaining more natural walking; and (2) traditional finite-state impedance control has difficulty adjusting parameters for different motions and users. In this paper, a flexible APK with a compact variable stiffness actuator (VSA) is designed for obtaining more flexible bionic characteristics. The VSA joint is implemented by two motors of different sizes, which connect the knee angle and the joint stiffness. Considering the complexity of prothetic lower limb control due to unknown APK dynamics, as well as strong coupling between biological joints and prosthetic joints, an adaptive robust force/position control method is designed for generating a desired gait trajectory of the prosthesis. It can operate without the explicit model of the system dynamics and multiple tuning parameters of different gaits. The proposed model-free scheme utilizes the time-delay estimation technique, sliding mode control, and fuzzy neural network to realize finite-time convergence and gait trajectory tracking. The virtual prototype of APK was established in ADAMS as a testing platform and compared with two traditional time-delay control schemes. Some demonstrations are illustrated, which show that the proposed method has superior tracking characteristics and stronger robustness under uncertain disturbances within the trajectory error in ± 0 . 5 degrees. The VSA joint can reduce energy consumption by adjusting stiffness appropriately. Furthermore, the feasibility of this method was verified in a human–machine hybrid control model.
Highlights
In the past decades, millions of people have had problems with the motion ability of their lower limbs due to wars, diseases, traffic accidents, and natural disasters
A new robust TDC scheme for the flexible joint is proposed to achieve improved tracking accuracy based on adaptive nonsingular fast terminal sliding mode control (ANFTSMC) without a sophisticated physical model or multi-tuning parameters
An adaptive robust force/position controller for flexible Active prosthetic knees (APKs) by using the time-delay estimation (TDE) technique combined with adaptive nonsingular fast terminal sliding mode control and fuzzy neural network is proposed
Summary
Millions of people have had problems with the motion ability of their lower limbs due to wars, diseases, traffic accidents, and natural disasters. Thanks to advances in actuation, microembedded computing, miniaturized sensing, energy storage, and automatic pattern recognition, many rehabilitative robots have been developed to help and recover human movement [2,3] To solve these limitations, APK, as a lower limb prosthesis, has drawn increasing research interests to help people deal with walking disabilities in the past years. An adaptive fractional-order nonsingular terminal sliding mode control with TDE scheme applied in joint tracking of manipulator is discussed [33]. A new robust TDC scheme for the flexible joint is proposed to achieve improved tracking accuracy based on adaptive nonsingular fast terminal sliding mode control (ANFTSMC) without a sophisticated physical model or multi-tuning parameters. An adaptive robust force/position controller for flexible APK by using the TDE technique combined with adaptive nonsingular fast terminal sliding mode control and fuzzy neural network is proposed.
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