Neural Approximation Enhanced Predictive Tracking Control of a Novel Designed Four-Wheeled Rollator
Abstract
:Featured Application
Abstract
1. Introduction
- To facilitate close to the requirements of the elderly or disabled users for assisted walking, according to the Kano and QFD model, a four-wheeled rollator that meets the travel needs of the elderly are innovatively designed by TRIZ theory.
- At the same time, the radial basis function neural network (RBFNN) approximation-based trajectory tracking control system is created to realize the high safety conditions of the assistant elderly walker system.
- The comparative tracking performance using classical MPC and the proposed neural-based model predictive control (NMPC) method is discussed, presenting availability for the users to move carefully and stably.
2. Novel Industrial Design for the Rollator
2.1. Product Innovation Model
- User interviews such as interviews and observations to conduct the needs research.
- The Kano model for user needs analysis.
- A quality house to convert user needs into technical features.
- TRIZ tool to solve product innovation.
2.2. The Mechanical Design of Elderly Rollator Based on an Industrial Innovation Method
3. Predictive Controller Design of the Rollator Based on Neural Approximation
3.1. Neural Approximation
3.2. The State Model of the Elderly Rollator
3.3. Predictive Controller Development
4. Results and Discussion
- Trajectory tracking co-simulation of the elderly rollator, including straight lines, curves, and obstacles, is intended to illustrate the position accuracy and robustness of the proposed NMPC algorithm.
- To further demonstrate the advantage of NMPC in uncertain disturbances for the assistive elderly walker, including internal mechanical friction and external rollator and human interaction forces, a contrast experiment using NMPC and MPC related to previous work [35], is discussed for the circular path.
5. Conclusions
6. Points for Future Discussion
Author Contributions
Funding
Conflicts of Interest
Abbreviations
MPC | Model Predictive Control |
RBFNN | Radial Basis Function Neural Network |
TRIZ | Theory of Inventive Problem Solving |
QFD | Quality Function Deployment |
HOQ | House of Quality |
PID | Proportion Integration Differentiation |
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Zhang, X.; Li, J.; Fan, K.; Chen, Z.; Hu, Z.; Yu, Y. Neural Approximation Enhanced Predictive Tracking Control of a Novel Designed Four-Wheeled Rollator. Appl. Sci. 2020, 10, 125. https://doi.org/10.3390/app10010125
Zhang X, Li J, Fan K, Chen Z, Hu Z, Yu Y. Neural Approximation Enhanced Predictive Tracking Control of a Novel Designed Four-Wheeled Rollator. Applied Sciences. 2020; 10(1):125. https://doi.org/10.3390/app10010125
Chicago/Turabian StyleZhang, Xin, Jiehao Li, Ke Fan, Ziyang Chen, Zhenhuan Hu, and Yu Yu. 2020. "Neural Approximation Enhanced Predictive Tracking Control of a Novel Designed Four-Wheeled Rollator" Applied Sciences 10, no. 1: 125. https://doi.org/10.3390/app10010125
APA StyleZhang, X., Li, J., Fan, K., Chen, Z., Hu, Z., & Yu, Y. (2020). Neural Approximation Enhanced Predictive Tracking Control of a Novel Designed Four-Wheeled Rollator. Applied Sciences, 10(1), 125. https://doi.org/10.3390/app10010125