Neural-Network-Based Robust Tracking Control for Condenser Cleaning Crawler-Type Mobile Manipulators with Delayed Uncert
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Neural-Network-Based Robust Tracking Control for Condenser Cleaning Crawler-Type Mobile Manipulators with Delayed Uncertainties Yi Zuo1 · Dong Hu2 · Yaonan Wang3 · Xinzhi Liu4 · Minghua Xie1 · Lihua Cao1 · Zhisheng Chen5 · Huimin Zhao5 Accepted: 9 November 2020 © Springer Nature B.V. 2020
Abstract In this paper, the problem of the robust tracking for two-arm condenser cleaning crawler-type mobile manipulators (CCCMM) with delayed angle-velocity uncertainties is original investigated. The two-arm condenser cleaning crawler-type mobile manipulators are composed of a crawler-type mobile platform and two-arm industrial manipulators.The uncertainty is nonlinear time-varying and does not require a matching condition. A wavelet transform and probabilistic neural network (WTPNN) system is used to approximate an unknown controlled system from the strategic manipulation of the model following tracking errors. Based on the Lyapunov method and the linear matrix inequality (LMI) approach, several sufficient conditions, which guarantee the state variables of the closed loop system to converge, globally, uniformly and exponentially, to a ball in the state space with any pre-specified convergence rate, are derived. Experiment results are given to illustrate the superior control performance of the proposed intelligent control method. Keywords Wavelet transform and probabilistic neural network · Time delays · Condenser cleaning · Crawler-type mobile manipulators · Lyapunov stability theorem · Robust tracking performance · Linear matrix inequality
1 Introduction This work was supported by the Changsha University Talent Introduction Research Project (2019), National Natural Science Foundation of China (51674042), Key Laboratory Foundation for Power Technology of Renewable Energy Sources of Hunan Province (2011KFJJ004), China Scholarship Council (201808430235), China Institute of Electrical Engineering Power Youth Science and Technology Innovation Projects (201014), Hunan Natural Science Foundation (2018JJ3561), Changsha Science and Technology Planning Project (k17005065), Hunan Education Authorities Science Research Project (16C0041, 17C0131), Hunan Education Authorities Science Research Outstanding Youth Project (20B057), the Young Teachers Program of Changsha University of Science and Technology (2019QJCZ041, 2019QJCZ079).
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Dong Hu [email protected]
1
The School of Electronic Information and Electrical Engineering, Changsha University, Changsha 410022, Hunan, People’s Republic of China
2
The School of Information Science and Engineering, Changsha Normal University, Changsha 410000, Hunan, People’s Republic of China
3
The College of Electric and Information Technology, Hunan University, Changsha 410082, Hunan, People’s Republic of China
The control problem of multi-joint manipulator and mobile robot has been paid a great attention for a long time, and many theoretical results have been reported [1–9]. However, most of the research works are focused on the control issues of the traditional manipulator [1] or mobile robot syste
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