scholarly journals Command-Filtered Backstepping Integral Sliding Mode Control with Prescribed Performance for Ship Roll Stabilization

2019 ◽  
Vol 9 (20) ◽  
pp. 4288 ◽  
Author(s):  
Zhongjia Jin ◽  
Weiming Zhang ◽  
Sheng Liu ◽  
Min Gu
Keyword(s):  
Sliding Mode Control ◽  
Controller Design ◽  
Sliding Mode ◽  
Tracking Error ◽  
Sea Waves ◽  
Prescribed Performance ◽  
Mode Control ◽  
Ship Roll ◽  
Roll Stabilization ◽  
Differential Expansion

In this paper, a novel, robust fin controller based on the backstepping control strategy and sliding mode control is proposed to handle the problem of ship roll stabilization. First, the mathematical model of the fin control system is established, including the modeling errors and the external disturbances generated by sea waves. In order to address the side effects caused by differential expansion, a command-filter is implemented within the backstepping controller design. By introducing a new performance function and a corresponding error transformation, the compensated tracking error can be bounded to achieve the desired prescribed dynamic and steady-state responses. The sliding mode disturbance rejection control with prescribed performance is realized by combining the disturbance observer. Simulations are presented to demonstrate the effectiveness of the proposed control scheme.

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.

scholarly journals Adaptive Sliding Mode Control Method for Z-Axis Vibrating Gyroscope Using Prescribed Performance Approach

2020 ◽  
Vol 10 (14) ◽  
pp. 4779 ◽  
Author(s):  
Cheng Lu ◽  
Liang Hua ◽  
Xinsong Zhang ◽  
Huiming Wang ◽  
Yunxiang Guo
Keyword(s):  
Sliding Mode Control ◽  
Error Bound ◽  
Control Method ◽  
Sliding Mode ◽  
Tracking Error ◽  
Adaptive Sliding Mode Control ◽  
Performance Control ◽  
Prescribed Performance ◽  
Adaptive Sliding Mode ◽  
Mode Control

This paper investigates one kind of high performance control methods for Micro-Electro-Mechanical-System (MEMS) gyroscopes using adaptive sliding mode control (ASMC) scheme with prescribed performance. Prescribed performance control (PPC) method is combined with conventional ASMC method to provide quantitative analysis of gyroscope tracking error performances in terms of specified tracking error bound and specified error convergence rate. The new derived adaptive prescribed performance sliding mode control (APPSMC) can maintain a satisfactory control performance which guarantees system tracking error, at any time, to be within a predefined error bound and the error convergences faster than the error bound. Besides, adaptive control (AC) technique is integrated with PPC to online tune controller parameters, which will converge to their true values at last. The stability of the control system is proved in the Lyapunov stability framework and simulation results on a Z-axis MEMS gyroscope is conducted to validate the effectiveness of the proposed control approach.

Adaptive prescribed performance sliding mode control of MEMS gyroscope

2016 ◽  
Vol 40 (2) ◽  
pp. 400-412 ◽  
Author(s):  
Cheng Lu ◽  
Juntao Fei
Keyword(s):  
Convergence Rate ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Tracking Error ◽  
Micro Electro Mechanical System ◽  
Performance Bound ◽  
Prescribed Performance ◽  
Mode Control ◽  
Performance Indexes ◽  
Adaptive Laws

An adaptive prescribed performance sliding mode control (APPSMC) of Micro-Electro-Mechanical System gyroscopes is proposed for the trajectory tracking in the presence of parameter variations and external disturbances. Steady-state error, transient error and convergence rate are important performance indexes in gyroscope systems. However, these indexes have not been investigated and corresponding control methods are not investigated as well. The proposed APPSMC scheme can guarantee that the tracking error is strictly within a predefined performance bound and the convergence rate is no less than a predefined value. All the gyroscope parameters including the angular velocity can be correctly estimated by adaptive laws and the disturbance bound is estimated by a neural network estimator to alleviate the chattering problem. Simulation results demonstrate the effectiveness of the proposed adaptive prescribed performance sliding mode controller.

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.

scholarly journals On Chattering-Free Dynamic Sliding Mode Controller Design

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Jeang-Lin Chang
Keyword(s):  
Sliding Mode Control ◽  
Controller Design ◽  
Sliding Mode ◽  
Control Law ◽  
Mode Control ◽  
Chattering Free ◽  
Dynamic Sliding Mode Control ◽  
System States ◽  
Dynamic Sliding Mode ◽  
Free Dynamic

For a class of linear MIMO uncertain systems, a dynamic sliding mode control algorithm that avoids the chattering problem is proposed in this paper. Without using any differentiator, we develop a modified asymptotically stable second-order sliding mode control law in which the proposed controller can guarantee the finite time convergence to the sliding mode and can show that the system states asymptotically approach to zero. Finally, a numerical example is explained for demonstrating the applicability of the proposed scheme.

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