Design of Closed-Loop Fuzzy FES Controller and Tests in Controlling Knee Extension Movements

Watanabe, Takashi; Tadano, Takeshi

doi:10.1587/transinf.2017edl8061

Cited by 10 publications

(17 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper, a closed-loop fuzzy FES controller was developed based on our previous study and a prototype of closed-loop FES control system for mobile FES cycling with the pedaling wheelchair was examined. Since FES control of mobile cycling depended on cycling system and there was no continuous time closed-loop FES controller for mobile cycling, a fuzzy controller was tested in controlling knee extension angle comparing to PID controller [17] and the developed prototype system was not compared with other control systems. Then, although ankle joint was controlled by FES during cycling without a orthotic brace, a closed-loop control for the ankle joint was not implemented.…”

Section: Discussionmentioning

confidence: 99%

“…The purpose of this study was to develop a prototype of closed-loop FES control system of cycling speed with the pedaling wheelchair and to test control performance of the controller in mobile FES cycling. First, a continuous time closed-loop fuzzy FES controller for cycling speed control was designed based on the fuzzy FES controller tested in knee extension angle control [17]. Since the controlled variable was different from the previous controller, control performance of the developed fuzzy controller had to be examined.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Experimental Tests of a Prototype of IMU-Based Closed-Loop Fuzzy Control System for Mobile FES Cycling with Pedaling Wheelchair

Watanabe

Tadano

2018

IEICE Trans. Inf. & Syst.

Self Cite

View full text Add to dashboard Cite

Rehabilitation training with pedaling wheelchair in combination with functional electrical stimulation (FES) can be effective for decreasing the risk of falling significantly. Automatic adjustment of cycling speed and making a turn without standstill has been desired for practical applications of the training with mobile FES cycling. This study aimed at developing closed-loop control system of cycling speed with the pedaling wheelchair. Considering clinical practical use with no requirement of extensive modifications of the wheelchair, measurement method of cycling speed with inertial motion measurement units (IMUs) was introduced, and fuzzy controller for adjusting stimulation intensity to regulate cycling speed was designed. The developed prototype of closed-loop FES control system achieved appropriately cycling speed for the different target speeds in most of control trials with neurologically intact subjects. In addition, all the control trials of low speed cycling including U-turn achieved maintaining the target speed without standstill. Cycling distance and cycling time increased with the closed-loop control of low cycling speed compensating decreasing of cycling speed caused by muscle fatigue. From these results, the developed closed-loop fuzzy FES control system was suggested to work reliably in mobile FES cycling.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experimental Tests of a Prototype of IMU-Based Closed-Loop Fuzzy Control System for Mobile FES Cycling with Pedaling Wheelchair

Watanabe

Tadano

2018

IEICE Trans. Inf. & Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, the Li et al (2017) [25] system settled with a little bit higher steady-state error (2 • ) compared to the FLC HDL system, which settled at a good steady-state error of 0.4 • and an overshoot of 1.2 • . For the reference angle of 20 • , the Watanabe et al (2017) [28] system performed with a relatively similar rise time and settling time but a higher steady-state error (0.6 • ) compared to the FLC HDL, which settled at 0.3 • to 0.4 • steady-state errors (for 40 • and 30 • reference angles). In comparison to all other developed systems, both the developed modelled FLC (FLC MAT) and the digital FLC (FLC HDL) are able to achieve low steady-state errors (0.3 • to 0.4 • ) and low system overshoot (1.2 • to 1.4 • ).…”

Section: System Level Verification (Hdl Co-simulation)mentioning

confidence: 94%

“…The performance of the designed digital FLC (FLC HDL) was further investigated and compared with other feedback controllers reported by other researchers, which include Benahmed et al (2017) [59], Lynch and Popovic (2012) [1], Li et al (2017) [25] and Watanabe et al (2017) [28]. Table 8 shows the key performance characteristics of the knee trajectory response, such as rise time, settling time, overshoot and steady-state error.…”

Section: System Level Verification (Hdl Co-simulation)mentioning

confidence: 99%

“…Therefore, the real-world FES device is expected to have the capability to regulate the pulse-to-pulse electrical stimulation in real-time to compensate for fatigue, muscle spasm, and retraining effects [ 1 , 22 , 24 , 25 ]. Several types of feedback controllers have been commonly used in the closed-loop FES system, which include Proportional-Integral-Derivative (PID) controller [ 1 , 27 , 28 , 29 ], Fuzzy Logic [ 7 , 8 , 18 , 19 , 28 , 30 , 31 , 32 , 33 , 34 ], Neuro Fuzzy [ 35 ], Sliding Mode Controller (SMC) [ 1 , 20 , 25 , 27 , 36 , 37 ], Gain Scheduling Controller (GSC) [ 38 ] and Artificial Neural Network (ANN) controller [ 36 , 39 ] and Adaptive Neuro Fuzzy Inference System (ANFIS) [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Design of an FPGA-Based Fuzzy Feedback Controller for Closed-Loop FES in Knee Joint Model

et al. 2021

View full text Add to dashboard Cite

Functional electrical stimulation (FES) device has been widely used by spinal cord injury (SCI) patients in their rehab exercises to restore motor function to their paralysed muscles. The major challenge of muscle contraction induced by FES is early muscle fatigue due to the open-loop stimulation strategy. To reduce the early muscle fatigue phenomenon, a closed-loop FES system is proposed to track the angle of the limb’s movement and provide an accurate amount of charge according to the desired reference angle. Among the existing feedback controllers, fuzzy logic controller (FLC) has been found to exhibit good control performance in handling complex non-linear systems without developing any complex mathematical model. Recently, there has been considerable interest in the implementation of FLC in hardware embedded systems. Therefore, in this paper, a digital fuzzy feedback controller (FFC) embedded in a field-programmable gate array (FPGA) board was proposed. The digital FFC mainly consists of an analog-to-digital converter (ADC) Data Acquisition and FLC sub-modules. The FFC was designed to monitor and control the progress of knee extension movement by regulating the stimulus pulse width duration to meet the target angle. The knee is expected to extend to a maximum reference angle setting (70°, 40° or 30°) from its normal position of 0° once the stimulus charge is applied to the muscle by the FES device. Initially, the FLC was modelled using MATLAB Simulink. Then, the FLC was hardcoded into digital logic using hardware description language (HDL) Verilog codes. Thereafter, the performance of the digital FLC was tested with a knee extension model using the HDL co-simulation technique in MATLAB Simulink. Finally, for real-time verification, the designed digital FFC was downloaded to the Intel FPGA (DE2-115) board. The digital FFC utilized only 4% of the total FPGA (Cyclone IV E) logic elements (LEs) and required 238 µs to regulate stimulus pulse width data, including 3 µs for the FLC computation. The high processing speed of the digital FFC enables the stimulus pulse width duration to be updated every stimulation cycle. Furthermore, the implemented digital FFC has demonstrated good control performance in accurately controlling the stimulus pulse width duration to reach the desired reference angle with very small overshoot (1.4°) and steady-state error (0.4°). These promising results are very useful for a real-world closed-loop FES application.

show abstract

A Type-2 Fuzzy PID-Based System of Surface FES with Pulse Width Modulation for Stroke Rehabilitation

Tian,

Chen,

Zhou

et al. 2023

2023 4th International Conference on Computer Engineering and Intelligent Control (ICCEIC)

View full text Add to dashboard Cite

Design of Closed-Loop Fuzzy FES Controller and Tests in Controlling Knee Extension Movements

Cited by 10 publications

References 11 publications

Experimental Tests of a Prototype of IMU-Based Closed-Loop Fuzzy Control System for Mobile FES Cycling with Pedaling Wheelchair

Experimental Tests of a Prototype of IMU-Based Closed-Loop Fuzzy Control System for Mobile FES Cycling with Pedaling Wheelchair

Design of an FPGA-Based Fuzzy Feedback Controller for Closed-Loop FES in Knee Joint Model

A Type-2 Fuzzy PID-Based System of Surface FES with Pulse Width Modulation for Stroke Rehabilitation

Contact Info

Product

Resources

About