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 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.

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 Neural Network PID Algorithm for a Class of Discrete-Time Nonlinear Systems

2018 ◽  
Vol 14 (02) ◽  
pp. 103 ◽  
Author(s):  
Huifang Kong ◽  
Yao Fang
Keyword(s):  
Neural Network ◽  
Nonlinear System ◽  
Sliding Mode Control ◽  
Discrete Time ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Model Parameters ◽  
Pid Algorithm ◽  
Mode Control ◽  
Model Free

<p class="0abstract"><span lang="EN-US">The control of nonlinear system is the hotspot in the control field. The paper proposes an algorithm to solve the tracking and robustness problem for the discrete-time nonlinear system. The completed control algorithm contains three parts. First, the dynamic linearization model of nonlinear system is designed based on Model Free Adaptive Control, whose model parameters are calculated by the input and output data</span><span lang="EN-US"> of system</span><span lang="EN-US">. Second, the model error is estimated using the Quasi-sliding mode control algorithm</span><span lang="EN-US">, hence, the whole model of system is estimated</span><span lang="EN-US">. Finally, the neural network </span><span lang="EN-US">PID </span><span lang="EN-US">controller is designed to get the optimal control law. The convergence and BIBO stability of the control system is proved by the Lyapunov function. The simulation results </span><span lang="EN-US">in</span><span lang="EN-US"> the </span><span lang="EN-US">linear and </span><span lang="EN-US">nonlinear system validate the effectiveness and robustness of the algorithm.</span><span lang="EN-US"> The robustness </span><span lang="EN-US">effort </span><span lang="EN-US">of </span><span lang="EN-US">Quasi-sliding mode control algorithm</span><span lang="EN-US"> in nonlinear system is also verified in the paper.</span></p>

scholarly journals Fractional-Order Iterative Sliding Mode Control Based on the Neural Network for Manipulator

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xin Zhang ◽  
Wenbo Xu ◽  
Wenru Lu
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Fractional Order ◽  
Control Strategy ◽  
Sliding Mode ◽  
Rbf Neural Network ◽  
Tracking Error ◽  
Position Tracking ◽  
Tracking Accuracy ◽  
Mode Control

This study aimed to improve the position tracking accuracy of the single joint of the manipulator when the manipulator model information is uncertain. The study is based on the theory of fractional calculus, radial basis function (RBF) neural network control, and iterative sliding mode control, and the RBF neural network fractional-order iterative sliding mode control strategy is proposed. First, the stability analysis of the proposed control strategy is carried out through the Lyapunov function. Second, taking the two-joint manipulator as an example, simulation comparison and analysis are carried out with iterative sliding mode control strategy, fractional-order iterative sliding mode reaching law control strategy, and fractional-order iterative sliding mode surface control strategy. Finally, through simulation experiments, the results show that the RBF neural network fractional-order iterative sliding mode control strategy can effectively improve the joints’ tracking and control accuracy, reduce the position tracking error, and effectively suppress the chattering caused by the sliding mode control. It is proved that the proposed control strategy can ensure high-precision position tracking when the information of the manipulator model is uncertain.

Adaptive Integral Non-Singular Terminal Sliding Mode Control of a Servo-Hydraulic System

2020 ◽  
Author(s):  
Yashar Shabbouei Hagh ◽  
Reza Mohammadi Asl ◽  
Heikki Handroos
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Hydraulic System ◽  
Sliding Mode ◽  
Control Signal ◽  
Terminal Sliding Mode Control ◽  
Hydraulic Actuator ◽  
Terminal Sliding Mode ◽  
Mode Control ◽  
System States

Abstract This paper proposes an adaptive integral non-singular terminal sliding mode control in combination with a neural network (INTSMC-NN) for nonlinear servo-hydraulic actuator systems. The proposed controller has the advantages of the conventional non-singular terminal sliding mode control; it can tolerate external disturbances, evades the singularity problem of the conventional terminal sliding mode control, and also guarantees finite time convergence of states. The main problem and drawback of the sliding mode-based control is the chattering phenomenon which is caused by the switching part of the controller. This phenomenon can cause severe impacts on mechanical components of the hydraulic system. In order to overcome to this issue, and moderate the control signal, the discontinuous part of the controller is replaced by a neural network. The stability of the controller is investigated through Lyapunov stability criteria. To study the performance of the proposed INTSMC in combination with neural network a third-order nonlinear servo-hydraulic actuator is considered. Simulation results first, indicates the capability of the proposed method in eliminating the chattering from the control signal and also making the system states to track the desired trajectory with high accuracy. Second, the performance of the proposed integral NTSMC is studied and compared to the conventional NTSMC.

scholarly journals Adaptive neural network terminal sliding mode control for uncertain spatial robot

2019 ◽  
Vol 16 (6) ◽  
pp. 172988141989406
Author(s):  
Chunxiang Sun ◽  
Guanjun Li ◽  
Jin Xu
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Tracking Error ◽  
Lyapunov Stability Theory ◽  
Small Region ◽  
Terminal Sliding Mode Control ◽  
Nonlinear Functions ◽  
Terminal Sliding Mode ◽  
Mode Control

The tracking control problem for uncertain spatial robot is investigated by means of adaptive terminal sliding mode control in this article. To approximate unknown nonlinear functions of these systems, a neural network model is employed. By using Lyapunov stability theory, adaptive terminal sliding mode controller is given, which guarantees that the tracking error converges to an arbitrary small region of zero and all the signals remain bounded. Finally, numerical simulation is given to confirm the effectiveness of the proposed method.

scholarly journals Design of Decentralized Adaptive Sliding Mode Controller for the Islanded AC Microgrid With Ring Topology

2021 ◽  
Vol 9 ◽  
Author(s):  
He Jiang ◽  
Mofan Wei ◽  
Yan Zhao ◽  
Ji Han
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Control Strategies ◽  
Tracking Error ◽  
Adaptive Sliding Mode Control ◽  
Linear Matrix ◽  
Error Performance ◽  
Ring Topology ◽  
Adaptive Sliding Mode ◽  
Mode Control

Sliding mode control can restrain the perturbations generated from the intermittence of the renewable energy generation and the randomness of local loads when microgrids are operating in islanded mode. However, the microgrid consists of several subsystems and the interactions among them will cause the chattering problems under the overall sliding mode control. In this paper, the chattering restraint issues for voltage control of the islanded microgrid with a ring topology structure are investigated based on the decentralized adaptive sliding mode control strategies. Firstly, we construct a tracking error system with interconnections considering the power transmission among subsystems and nominal values of system states. Secondly, we design linear matrix inequalities (LMIs) according to the H∞ attenuation performance of the system external disturbances. Then, the tracking error performance and the control precision are guaranteed via the asymptotic stabilities of integral sliding mode surfaces. Adaptive laws are utilized to address the chattering problems of the sliding mode control. Finally, simulation results verify the effectiveness of the proposed decentralized control methods.

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.

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