Fuzzy CMAC-Based Adaptive Scale Force Control of Body Weight Support Exoskeletons

Wu, Han; An, Honglei; Wei, Qing; Ma, Hongxu

doi:10.1109/access.2020.3013417

Cited by 7 publications

(2 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Xuw studied fuzzy controller for autonomous vehicles based on coarse sets [19]. Wu examined fuzzy cmac based adaptive scale force control of exoskeletons weight support [20].…”

Section: Extended Fuzzy Adaptive Event Trigger Compensationmentioning

confidence: 99%

Second Order Integral Fuzzy Logic Control Based Rocket Tracking Control

Iswanto

Ahmad

2021

jrc

View full text Add to dashboard Cite

Fuzzy logic is a logic with a degree of vulnerability ranging from 0 to 1. Fuzzy logic is used to convert a quantity into language. It is used as a control system because it is a versatile and simple control process that does not require complex mathematical models. The paper aimed to present a fuzzy control system implemented in a rocket tracking control system as the controller because it could work well on non-linear systems and offered convenience in program design. The fuzzy control system worked to keep the rocket on track and travel at a fixed speed. The signal from the fuzzy logic control system served to control the rocket thrust. However, the process of the fuzzy logic control system is slow and time-consuming, not proper for the one that required rapid control, such as rockets, and is not applicable for tracking ramp and parabolic signals. The fuzzy logic, therefore, was modified by adding second-order integral control. The proposed algorithm showed that, by adding second-order integral control, the rocket glided 12.78m at 12 seconds with a steady-state error of 0.78 according to the setpoint of ramp path 12 m; 10.68m at 10 seconds with a steady-state error of 0.68 according to the setpoint of ramp path 10m; and 4.689m at 4 seconds with a steady-state error of 0.689 according to the setpoint of ramp path 4m. In accordance with the parabolic path, the rocket glided 15.47m at the 4th minute with 0 steady-state error.

show abstract

“…Xuw studied fuzzy controller for autonomous vehicles based on coarse sets [19]. Wu examined fuzzy cmac based adaptive scale force control of exoskeletons weight support [20].…”

Section: Extended Fuzzy Adaptive Event Trigger Compensationmentioning

confidence: 99%

Second Order Integral Fuzzy Logic Control Based Rocket Tracking Control

Iswanto

Ahmad

2021

jrc

View full text Add to dashboard Cite

show abstract

“…Typical examples include the sensitivity amplification control (SAC) 7 and fictitious gain method. 8 Another line of thought is to design a cascade force controller with human-machine interaction force measured, such as adaptive scale force control, 9 proportional-integral-derivative (PID) admittance control 10 and human-robot cooperation control. 11 To overcome the negative effect of various model uncertainties and disturbances in the exoskeleton systems, some robust control methods are also proposed, such as the disturbance observer-based impedance control, 12 adaptive assist-as-needed control 13 and adaptive sliding mode control.…”

Section: Introductionmentioning

confidence: 99%

Precision force control of an underactuated stance leg exoskeleton for human performance augmentation

Chen

Han

Dong

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

Lower limb exoskeleton which augments the human performance is a wearable human–machine integrated system used to assist people carrying heavy loads. Recently, underactuated lower limb exoskeleton systems with some passive joints become more and more attractive due to the advantages of smaller weight, lower system energy consumption and lower cost. However, because of the less of control inputs, the existed control methods of fully actuated exoskeletons cannot be extended to underactuated systems, which makes the robust controller design of underactuated lower limb exoskeletons becomes more challenged. This article focuses on the high-performance human–machine interaction force control design of underactuated lower limb exoskeletons with passive ankle joint. In order to solve the reduction of control inputs, the holonomic constraint from the wearer is considered, which help transform the dynamics of 3-degree-of-freedom underactuated exoskeleton in joint space into a 2-degree-of-freedom fully actuated system in Cartesian space. A two-level interaction force controller using adaptive robust control algorithm is proposed to effectively address the negative effect of various model uncertainties and external disturbances. In order to facilitate the control parameter selection, a gain tuning method is also presented. Comparative simulations are carried out, which indicate that the proposed two-level interaction force controller achieves smaller interaction force and better robust performance to various modeling errors and disturbances.

show abstract