Novel adaptive fuzzy control for pendubot with actuator faults and uncertainties: Design and experiments

Pendubot has been widely applied as a benchmark platform for control research and education. In this paper, a novel adaptive fuzzy hierarchical sliding mode controller (AFHSMC) is proposed for the pendubot under actuator faults and uncertainties. The proposed controller is designed by combining hierarchical sliding mode control (HSMC), fuzzy logic control (FLC), and balancing composite motion optimization. The proposed controller preserves many advantages such as having a straightforward structure, simple implementation, chattering reduction, and high precision and robustness. The stability of the proposed controller is ensured by using the Lyapunov approach. To verify the control performance, various numerical simulations and experiments are conducted on a pendubot under conditions that involve actuator faults and uncertainties. Compared to the conventional HSMC and FHSMC controllers, the proposed AFHSMC improves by 0.43% and 0.38% for tracking precision of the first link's angle estimate, 3.26% and 0.08% for the second link's angle estimate when influenced by uncertainties, as well as 65.23% and 12.24% for the first link, 83.95% and 16.15% for the second link when influenced by faults. • The proposed approach integrates HSMC and FLCs to tune the sliding gain and approximate uncertainties. • The BCMO method is proposed for optimizing the proposed controller, hence it is simple and easy to implement. • The proposed AHSMC controller offers advantages like simplicity, chatter-free operation, and high precision. • The proposed controller outperforms both HSMC and FHSMC in simulations and experiments on the pendubot.

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Publication Details

Journal
Results in Engineering
Published
2024-09-23
DOI
https://doi.org/10.1016/j.rineng.2024.102916
Citations
7
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
2.30

Funders

Controls
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article

Novel adaptive fuzzy control for pendubot with actuator faults and uncertainties: Design and experiments

Duc-Hung Pham, Van‐Truong Nguyen, Mien Van, Van-Tuan Nguyen et al.
7 citations
Results in Engineering
Adaptive Control of Nonlinear Systems
2.30
article

Novel adaptive fuzzy control for pendubot with actuator faults and uncertainties: Design and experiments

Duc-Hung Pham, Van‐Truong Nguyen, Mien Van, Van-Tuan Nguyen, Duc-Canh Nguyen, Quoc Cuong Nguyen
article en
7 citations

Abstract

Pendubot has been widely applied as a benchmark platform for control research and education. In this paper, a novel adaptive fuzzy hierarchical sliding mode controller (AFHSMC) is proposed for the pendubot under actuator faults and uncertainties. The proposed controller is designed by combining hierarchical sliding mode control (HSMC), fuzzy logic control (FLC), and balancing composite motion optimization. The proposed controller preserves many advantages such as having a straightforward structure, simple implementation, chattering reduction, and high precision and robustness. The stability of the proposed controller is ensured by using the Lyapunov approach. To verify the control performance, various numerical simulations and experiments are conducted on a pendubot under conditions that involve actuator faults and uncertainties. Compared to the conventional HSMC and FHSMC controllers, the proposed AFHSMC improves by 0.43% and 0.38% for tracking precision of the first link's angle estimate, 3.26% and 0.08% for the second link's angle estimate when influenced by uncertainties, as well as 65.23% and 12.24% for the first link, 83.95% and 16.15% for the second link when influenced by faults. • The proposed approach integrates HSMC and FLCs to tune the sliding gain and approximate uncertainties. • The BCMO method is proposed for optimizing the proposed controller, hence it is simple and easy to implement. • The proposed AHSMC controller offers advantages like simplicity, chatter-free operation, and high precision. • The proposed controller outperforms both HSMC and FHSMC in simulations and experiments on the pendubot.

Results in EngineeringVol. 24
Queen's University Belfast (GB), Hung Yen University of Technology and Education (VN), Artificial Intelligence in Medicine (Canada) (CA), Hanoi University of Industry (VN), Yuan Ze University (TW)
Tập đoàn Vingroup - Công ty CP, Quỹ Đổi mới sáng tạo Vingroup
Climate action
Openalex Percentile: Top 11%
Adaptive Control of Nonlinear Systems
2.30
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