Barrier Lyapunov function based adaptive region tracking control for underwater vehicles with thruster saturation and dead zone

2021 ◽  
Author(s):  
Xing Liu ◽  
Mingjun Zhang ◽  
Feng Yao ◽  
Baoji Yin ◽  
Junwei Chen
Keyword(s):  
Lyapunov Function ◽  
Tracking Control ◽  
Dead Zone ◽  
Underwater Vehicles ◽  
Barrier Lyapunov Function ◽  
Region Tracking

Adaptive control based on Barrier Lyapunov function for a class of full-state constrained stochastic nonlinear systems with dead-zone and unmodeled dynamics

2021 ◽  
pp. 014233122098563
Author(s):  
Fei Shen ◽  
Xinjun Wang ◽  
Xinghui Yin
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Lyapunov Function ◽  
Dead Zone ◽  
Small Neighborhood ◽  
Unmodeled Dynamics ◽  
Stochastic Nonlinear Systems ◽  
Dynamic Surface ◽  
Barrier Lyapunov Function ◽  
Full State

This paper investigates the problem of adaptive control based on Barrier Lyapunov function for a class of full-state constrained stochastic nonlinear systems with dead-zone and unmodeled dynamics. To stabilize such a system, a dynamic signal is introduced to dominate unmodeled dynamics and an assistant signal is constructed to compensate for the effect of the dead zone. Dynamic surface control is used to solve the “complexity explosion” problem in traditional backstepping design. Two cases of symmetric and asymmetric Barrier Lyapunov functions are discussed respectively in this paper. The proposed Barrier Lyapunov function based on backstepping method can ensure that the output tracking error converges in the small neighborhood of the origin. This control scheme can ensure that semi-globally uniformly ultimately boundedness of all signals in the closed-loop system. Two simulation cases are proposed to verify the effectiveness of the theoretical method.

Barrier Lyapunov function-based adaptive output feedback failure compensation for a class of non-linear systems with unknown dead-zone non-linearity

2016 ◽  
Vol 39 (8) ◽  
pp. 1169-1181 ◽  
Author(s):  
Yuefei Wu ◽  
Jianyong Yao
Keyword(s):  
Lyapunov Function ◽  
Output Feedback ◽  
Dead Zone ◽  
Output Feedback Control ◽  
Control Law ◽  
Unknown Input ◽  
Barrier Lyapunov Function ◽  
Non Linear ◽  
Bounded Disturbances ◽  
Non Linear Systems

In this paper, an adaptive robust output feedback control approach is proposed for a class of uncertain non-linear systems with unknown input dead-zone non-linearity, unknown failures and unknown bounded disturbances. By constructing the dead-zone inverse and applying the backstepping recursive design technique, a robust adaptive backstepping controller is proposed, in which adaptive control law is synthesized to handle parametric uncertainties and a novel robust control law to attenuate disturbances. The robust output feedback control law is developed by integrating a switching function σ algorithm at each step of the backstepping design procedure. In addition, K-filters are designed to estimate the unmeasured states and neural networks are employed to approximate the unknown non-linear functions. By ensuring boundedness of the barrier Lyapunov function, the major feature of the proposed controller is that it can theoretically guarantee asymptotic output tracking performance, in spite of the presence of unknown input dead-zone non-linearity, various actuator failures and unknown bounded disturbances via Lyapunov stability analysis. The effectiveness of the proposed approach is illustrated by the simulation examples.

Tracking Control for Switched Nonlinear Systems Subject to Time-Varying Output Constraints

2012 ◽  
Author(s):  
Ben Niu ◽  
Georgi M. Dimirovski ◽  
Jun Zhao
Keyword(s):  
Nonlinear Systems ◽  
Lyapunov Function ◽  
Tracking Control ◽  
Closed Loop ◽  
Time Varying ◽  
Switched Nonlinear Systems ◽  
Feedback Form ◽  
Barrier Lyapunov Function ◽  
Output Constraints ◽  
Asymptotic Tracking

In this paper, we address the tracking control problem for switched nonlinear systems in strict-feedback form with time-varying output constraints. To prevent the output from violating the time-varying constraints, we employ a Barrier Lyapunov Function, which relies explicitly on time. Based on the simultaneous domination assumption, we design a controller for the switched system, which guarantees that asymptotic tracking is achieved without transgression of the constraints and all closed-loop signals remain bounded under arbitrary switchings. The effectiveness of the proposed results is illustrated using a numerical example.

scholarly journals Robust Prescribed Performance Control of Uncertain Vehicle Lateral System under State Constraints

2021 ◽  
Vol 2083 (3) ◽  
pp. 032029
Author(s):  
Jing Yu
Keyword(s):  
Neural Network ◽  
Control System ◽  
Lyapunov Function ◽  
Finite Time ◽  
Tracking Control ◽  
State Constraints ◽  
Tracking Error ◽  
Lateral Control ◽  
Barrier Lyapunov Function ◽  
The Neural Network

Abstract In the study of the zero-error tracking control problem for vehicle lateral control systems under full-state constraints and nonparametric uncertainties, the zero-error tracking control problem is presented in this paper. A neural adaptive tracking control scheme is proposed by combining the error transformation of the vehicle lateral control system with the barrier Lyapunov function, which realizes that the tracking error of the vehicle lateral control converges to a prescribed compact set at a controllable or specified convergence rate in a specified finite time. The scheme has the following significant characteristics: 1) Based on the Nussbaum gain, the preset new energy finite-time control algorithm, the tracking error of the vehicle lateral control system with non-parametric uncertainty and external disturbance decreases to zero with t → ∞. In addition, it also has the control ability to cope with the presence or even unknown moment of inertia of the system. 2) Barrier Lyapunov function (BLF) ensures the bounded input of the neural network during the whole system envelope, and ensures the stable learning and approximation of the neural network. Furthermore, the bounded stability of the closed-loop system is proved by Lyapunov analysis. Finally, the effectiveness and superiority of the proposed control method are verified by simulation.

Three Dimensional Path Planning of Autonomous Underwater Vehicles

2013 ◽  
Vol 328 ◽  
pp. 128-132
Author(s):  
Yan Peng ◽  
Wei Qing Wu ◽  
Mei Liu ◽  
Shao Rong Xie ◽  
Jun Luo
Keyword(s):  
Lyapunov Function ◽  
Path Planning ◽  
Real Time ◽  
Tracking Control ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Three Dimensional ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Control Lyapunov Function

The path planning relates to the safe movement and navigation of the Autonomous Underwater Vehicles (AUV). This paper discusses the way of real-time path planning for autonomous underwater vehicle based on tracking control lyapunov function. The simulation conducted on H300 illustrates the effectiveness of proposed method.

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