Adaptive interval type-2 fuzzy control for multi-legged underwater robot with input saturation and full-state constraints

Abstract

In this paper, a trajectory tracking control strategy is proposed for multi-legged underwater robot in the presence of input saturation and full-state constraints. An anti-windup compensator is introduced to solve the input saturation problem, which can compensate for the saturation difference directly. Besides, the state constrains are addressed by a new state saturation function and the external unknown disturbances are solved by interval type-2 fuzzy neural network approximator. The dynamic surface control method combines with backstepping method is utilised to construct Lyapunov function. The control law and signals of the closed-loop system can be guaranteed to achieve semi-global uniform boundedness. Numerical simulations are presented to show the effectiveness of the proposed algorithm.

KEYWORDS:

• Multi-legged underwater robot
• anti-windup compensator
• interval type-2 fuzzy neural network
• dynamic surface control
• full-state constraints

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Natural Science Foundation of China [grant numbers U1713205, 61803119, 61673239, 61703228, and 62073183] and the Research Fund from Science and Technology on Underwater Vehicle Laboratory [grant number 6142215180208].

Notes on contributors

Yanchao Sun

Yanchao Sun received his BS degree in Flight Vehicle Design and Engineering, and MS degree and PhD degree in Control Science and Engineering from Harbin Institute of Technology, Harbin, China in 2010, 2012, and 2016, respectively. He is currently an Associate Professor of Science and Technology on Underwater Vehicle Laboratory at the Harbin Engineering University. His research interests include distributed cooperative control of multiple Euler–Lagrange systems, multi-agent system control, and multiple AUV systems control.

Xinyan Chen

Xinyan Chen is working toward the MS degree in naval architecture and ocean engineering at the Harbin Engineering University. His research interests include bionic robot system control and nonlinear control.

Ziwei Wang

Ziwei Wang received the BS degree from the Department of Control Science and Technology, Harbin Institute of Technology, China, in 2016. He received the PhD degree from the Department of Automation, Tsinghua University, Beijing, China, in 2020. He is currently a research associate with Human Robotics Group, the Department of Bioengineering, Imperial College London, U.K. His current research interests include bilateral teleoperation, fuzzy control, and human-machine systems.

Hongde Qin

Hongde Qin received the PhD degree from Harbin Engineering University, Harbin, China in 2003. He is a Professor and Director of Science and Technology on Underwater Vehicle Laboratory at the Harbin Engineering University. His current research interest involves underwater vehicle system control and bionic robot system control.

Ruijie Jing

Ruijie Jing is working toward the MS degree in naval architecture and ocean engineering at the Harbin Engineering University. His research interests include AUV systems control and nonlinear control.