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Your search keyword '"Li, Han-Xiong"' showing total 15 results
Start Over Author "Li, Han-Xiong" Journal ieee transactions on industrial electronics
15 results on '"Li, Han-Xiong"'

4. Confidence-Aware Multiscale Learning for Online Modeling of Distributed Parameter Systems With Application to Curing Process

Author

Meng, Xian-Bing, Chen, C. L. Philip, and Li, Han-Xiong

Abstract

In industrial applications, the modeling of distributed parameter systems (DPSs) is of significance for process control and monitoring. Due to infinite dimension, spatiotemporal coupled dynamics, nonlinearity, and model uncertainties, however, modeling and online applications of DPSs are very difficult. To address these issues, an online spatiotemporal modeling method is proposed based on confidence-aware multiscale learning. From the spacial-scale perspective, an evolutionary learning-based spatial basis function is designed by learning from two dimensionality reduction methods, including Karhunen–Lo$\grave{e}$ ve and diffusion maps. From the temporal-scale perspective, an efficient broad learning system is developed as reduced-order model to online address temporal dynamics of DPSs. As for the spatiotemporal-scale learning, Gaussian process regression is proposed as confidence-aware estimator to compensate for model generalization errors caused by spatiotemporal coupled dynamics. Through integration with the three-scale learning, the proposed method enables online confidence-aware prediction for DPSs. Experiments based on the curing process in snap curing oven demonstrate the effectiveness of proposed method.

Published
2023
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8. Neuro-fuzzy dynamic-inversion-based adaptive control for robotic manipulators--discrete time case

Author

Sun, Fuchun, Li, Li, Li, Han-Xiong, and Liu, Huaping

Subjects
Fuzzy algorithms -- Usage, Fuzzy logic -- Usage, Fuzzy systems -- Usage, Discrete-time systems -- Research, Adaptive control -- Research, Robots -- Control systems, Robots -- Research, Fuzzy logic, Business, Computers, Electronics, Electronics and electrical industries
Abstract

In this paper, we present a stable discrete-time adaptive tracking controller using a neuro-fuzzy (NF) dynamic-inversion for a robotic manipulator with its dynamics approximated by a dynamic T-S fuzzy model. The NF dynamic-inversion constructed by a dynamic NF (DNF) system is used to compensate for the robot inverse dynamics for a better tracking performance. By assigning the dynamics of the DNF system, the dynamic performance of a robot control system can be guaranteed at the initial control stage, which is very important for enhancing system stability and adaptive learning. The discrete-time adaptive control composed of the NF dynamic-inversion and NF variable structure control (NF-VSC) is developed to stabilize the closed-loop system and ensure the high-quality tracking. The NF-VSC enhances the stability of the controlled system and improves the system dynamic performance during the NF learning. The system stability and the convergence of tracking errors are guaranteed by the Lyapunov stability theory, and the learning algorithm for the DNF system is obtained thereby. An example is given to show the viability and effectiveness of the proposed control approach. Index Terms--Adaptive control, dynamic-inversion, neurofuzzy (NF) systems, NF variable structure, robotic manipulators.

Published
2007

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