scholarly journals Path Following of Autonomous Vehicle in 2D Space Using Multivariable Sliding Mode Control

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Daxiong Ji ◽  
Jian Liu ◽  
Hongyu Zhao ◽  
Yiqun Wang
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Autonomous Vehicle ◽  
Tracking Error ◽  
Small Neighborhood ◽  
Path Following ◽  
Parametric Uncertainty ◽  
Parametric Modeling ◽  
Mode Control ◽  
2D Space

A solution to the path following problem for underactuated autonomous vehicles in the presence of possibly large modeling parametric uncertainty is proposed. For a general class of vehicles moving in 2D space, we demonstrated a path following control law based on multiple variable sliding mode that yields global boundedness and convergence of the position tracking error to a small neighborhood and robustness to parametric modeling uncertainty. An error integration element is added into the “tanh” function of the traditional sliding mode control. We illustrated our results in the context of the vehicle control applications that an underwater vehicle moves along with the desired paths in 2D space. Simulations show that the control objectives were accomplished.

scholarly journals Adaptive compound second-order terminal sliding mode control for the longitudinal attitude control of the fully submerged hydrofoil vessel

2019 ◽  
Vol 11 (12) ◽  
pp. 168781401989563 ◽  
Author(s):  
Sheng Liu ◽  
Hongmin Niu ◽  
Lanyong Zhang ◽  
Xiaojie Guo
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Tracking Error ◽  
Small Neighborhood ◽  
Second Order ◽  
Terminal Sliding Mode Control ◽  
Terminal Sliding Mode ◽  
Fast Tracking ◽  
Mode Control ◽  
The Stability

Due to the ever-existing environmental disturbance of ocean wave and nonlinear of the system, it is difficult to obtain a satisfying control performance for the longitudinal attitude and desired height tracking of the fully submerged hydrofoil vessel. To solve such problems, an adaptive compound second-order terminal sliding mode controller is proposed. First, a combination of the complementary sliding mode surface and second-order terminal sliding mode control is introduced. Therefore, the closed system is uniformly ultimately bounded, and the steady-state errors converge to a small neighborhood of equilibrium point. Second, the chattering problem in an actual controller is solved by eliminating the sign function contained in the controller after integration without influencing the stability of the closed-loop system. Besides, a revised adaptive radial basis function neural network is introduced to estimate the derivative of the unknown environmental disturbances without the prior information of the disturbance. Finally, the stability of the system is proved by the Lyapunov stability theory. Numerical experimental results demonstrate that the proposed method possesses fast tracking ability and can decrease the stabilization error and the tracking error simultaneously.

scholarly journals Observer-based adaptive neural network backstepping sliding mode control for switched fractional order uncertain nonlinear systems with unmeasured states

2021 ◽  
pp. 002029402110211
Author(s):  
Tao Chen ◽  
Damin Cao ◽  
Jiaxin Yuan ◽  
Hui Yang
Keyword(s):  
Neural Network ◽  
Nonlinear Systems ◽  
Sliding Mode Control ◽  
Fractional Order ◽  
Sliding Mode ◽  
Tracking Error ◽  
Adaptive Neural Network ◽  
Dynamic Surface ◽  
Mode Control ◽  
The Stability

This paper proposes an observer-based adaptive neural network backstepping sliding mode controller to ensure the stability of switched fractional order strict-feedback nonlinear systems in the presence of arbitrary switchings and unmeasured states. To avoid “explosion of complexity” and obtain fractional derivatives for virtual control functions continuously, the fractional order dynamic surface control (DSC) technology is introduced into the controller. An observer is used for states estimation of the fractional order systems. The sliding mode control technology is introduced to enhance robustness. The unknown nonlinear functions and uncertain disturbances are approximated by the radial basis function neural networks (RBFNNs). The stability of system is ensured by the constructed Lyapunov functions. The fractional adaptive laws are proposed to update uncertain parameters. The proposed controller can ensure convergence of the tracking error and all the states remain bounded in the closed-loop systems. Lastly, the feasibility of the proposed control method is proved by giving two examples.

Fuzzy Sliding-Mode Control of a Variable Geometry Manipulator: Experimental Investigation

2000 ◽  
Author(s):  
J. Choi ◽  
C. W. de Silva ◽  
V. J. Modi ◽  
A. K. Misra
Keyword(s):  
Fuzzy Logic ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Tracking Error ◽  
Experimental Studies ◽  
Sliding Mode Controller ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Knowledge Based ◽  
Fuzzy Sliding Mode

Abstract This paper focuses a robust and knowledge-based control approach for multi-link robot manipulator systems. Based on the concepts of sliding-mode control and fuzzy logic control (FLC), a fuzzy sliding-mode controller has been developed in previous work. This controller possesses good robustness properties of sliding-mode control and the flexibility and ‘intelligent’ capabilities of knowledge-based control through the use of fuzzy logic. This paper presents experimental studies with fuzzy sliding-mode control as well as conventional sliding-mode control. The results show that the tracking error is guaranteed to converge to a specification in the presence of uncertainties. The performance of the fuzzy sliding-mode controller is found to be somewhat better than that of the conventional sliding-mode controller.

scholarly journals Neural Network Identification and Sliding Mode Control for Hysteresis Nonlinear System with Backlash-Like Model

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Ruiguo Liu ◽  
Xuehui Gao
Keyword(s):  
Neural Network ◽  
Nonlinear System ◽  
Sliding Mode Control ◽  
Controller Design ◽  
Sliding Mode ◽  
Control Strategies ◽  
Tracking Error ◽  
Mode Control ◽  
Hysteresis Nonlinearity ◽  
System States

A new neural network sliding mode control (NNSMC) is proposed for backlash-like hysteresis nonlinear system in this paper. Firstly, only one neural network is designed to estimate the unknown system states and hysteresis section instead of multiscale neural network at former researches since that can save computation and simplify the controller design. Secondly, a new NNSMC is proposed for the hysteresis nonlinearity where it does not need tracking error transformation. Finally, the Lyapunov functions are adopted to guarantee the stabilities of the identification and control strategies semiglobally uniformly ultimately bounded (UUB). Two cases simulations are proved the effectiveness of the presented identification approach and the performance of the NNSMC.

scholarly journals Output Feedback Adaptive Dynamic Surface Sliding-Mode Control for Quadrotor UAVs with Tracking Error Constraints

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-23 ◽  
Author(s):  
Guoqiang Zhu ◽  
Sen Wang ◽  
Lingfang Sun ◽  
Weichun Ge ◽  
Xiuyu Zhang
Keyword(s):  
Sliding Mode Control ◽  
Output Feedback ◽  
Controller Design ◽  
Sliding Mode ◽  
Tracking Error ◽  
Control Process ◽  
Nonlinear Observer ◽  
Dynamic Surface ◽  
Mode Control ◽  
Control Scheme

In this paper, a fuzzy adaptive output feedback dynamic surface sliding-mode control scheme is presented for a class of quadrotor unmanned aerial vehicles (UAVs). The framework of the controller design process is divided into two stages: the attitude control process and the position control process. The main features of this work are (1) a nonlinear observer is employed to predict the motion velocities of the quadrotor UAV; therefore, only the position signals are needed for the position tracking controller design; (2) by using the minimum learning technology, there is only one parameter which needs to be updated online at each design step and the computational burden can be greatly reduced; (3) a performance function is introduced to transform the tracking error into a new variable which can make the tracking error of the system satisfy the prescribed performance indicators; (4) the sliding-mode surface is introduced in the process of the controller design, and the robustness of the system is improved. Stability analysis proved that all signals of the closed-loop system are uniformly ultimately bounded. The results of the hardware-in-the-loop simulation validate the effectiveness of the proposed control scheme.

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