scholarly journals Friction Compensation Control of Electromechanical Actuator Based on Neural Network Adaptive Sliding Mode

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1508
Author(s):  
Wei Ruan ◽  
Quanlin Dong ◽  
Xiaoyue Zhang ◽  
Zhibing Li
Keyword(s):  
Neural Network ◽  
Sliding Mode ◽  
Dynamic Performance ◽  
External Disturbance ◽  
Sliding Mode Controller ◽  
Electromechanical Actuator ◽  
Adaptive Sliding Mode ◽  
Adaptive Sliding Mode Controller ◽  
Radial Basis ◽  
Actuator System

In this paper, a radial basis neural network adaptive sliding mode controller (RBF−NN ASMC) for nonlinear electromechanical actuator systems is proposed. The radial basis function neural network (RBF−NN) control algorithm is used to compensate for the friction disturbance torque in the electromechanical actuator system. An adaptive law was used to adjust the weights of the neural network to achieve real−time compensation of friction. The sliding mode controller is designed to suppress the model uncertainty and external disturbance effects of the electromechanical actuator system. The stability of the RBF−NN ASMC is analyzed by Lyapunov’s stability theory, and the effectiveness of this method is verified by simulation. The results show that the control strategy not only has a better compensation effect on friction but also has better anti−interference ability, which makes the electromechanical actuator system have better steady−state and dynamic performance.

scholarly journals Friction compensation and observer-based adaptive sliding mode control of electromechanical actuator

2018 ◽  
Vol 10 (12) ◽  
pp. 168781401881379 ◽  
Author(s):  
Mingyue Zhang ◽  
Man Zhou ◽  
Hui Liu ◽  
Baiqiang Zhang ◽  
Yulian Zhang ◽  
...  
Keyword(s):  
Model Uncertainty ◽  
Sliding Mode ◽  
Friction Torque ◽  
Friction Compensation ◽  
Sliding Mode Controller ◽  
Electromechanical Actuator ◽  
Adaptive Sliding Mode ◽  
Model Based ◽  
Adaptive Sliding Mode Controller ◽  
Actuator System

The performance of the electromechanical actuator system is usually affected by the nonlinear friction torque disturbance, model uncertainty, and unknown disturbances. In order to solve this problem, a model-based friction compensation method combined with an observer-based adaptive sliding mode controller for the speed loop of electromechanical actuator system is presented in this article. All the disturbances and model uncertainty of electromechanical actuator system are divided into two parts. One is model-based friction torque disturbance which can be identified by experiments, and the other is the residual disturbance which cannot be identified by experiments. A modified LuGre model is adopted to describe the friction torque disturbance of electromechanical actuator system. An extended state observer is designed to estimate the residual disturbance. An adaptive sliding mode controller is designed to control the system and compensate the friction torque disturbance and the residual disturbance. The stability of the electromechanical actuator system is discussed with Lyapunov stability theory and Barbalat’s lemma. Experiments are designed to validate the proposed method. The results demonstrate that the proposed control strategy not only provides better disturbance rejecting ability but also provides better steady state and dynamic performance.

Sliding mode control of a shape memory alloy actuated active flexible needle

Robotica ◽  
2018 ◽  
Vol 36 (8) ◽  
pp. 1188-1205 ◽  
Author(s):  
Felix Orlando Maria Joseph ◽  
Tarun Podder
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Sliding Mode ◽  
External Disturbance ◽  
Sliding Mode Controller ◽  
Precise Control ◽  
Adaptive Sliding Mode ◽  
Tissue Phantom ◽  
Adaptive Sliding Mode Controller ◽  
Actual Movement

SUMMARYIn medical interventional procedures such as brachytherapy, biopsy and radio-frequency ablation, precise tracking through the preplanned desired trajectory is very essential. This important requirement is critical due to two major reasons: anatomical obstacle avoidance and accurate targeting for avoiding undesired radioactive dose exposure or damage to neighboring tissue and critical organs. Therefore, a precise control of the needling device in the unstructured environment in the presence of external disturbance is required to achieve accurate target reaching in clinical applications. In this paper, a shape memory alloy actuated active flexible needle controlled by an adaptive sliding mode controller is presented. The trajectory tracking performance of the needle is tested while having its actual movement in an artificial tissue phantom by giving various input reference trajectories such as multi-step and sinusoidal. Performance of the adaptive sliding mode controller is compared with that of the proportional, integral and derivative controller and is proved to be the effective method in the presence of the external disturbances.

Gain adaptive sliding mode controller based on interval type-II fuzzy neural network designed for attitude control for micro aircraft vehicle

2014 ◽  
Vol 7 (2) ◽  
pp. 209-226 ◽  
Author(s):  
Xiangjian Chen ◽  
Di Li ◽  
Zhijun Xu ◽  
Yue Bai
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Type Ii ◽  
Content Type ◽  
Adaptive Sliding Mode ◽  
Adaptive Sliding Mode Controller ◽  
Fuzzy Neural ◽  
Interval Type

Purpose – Micro aerial vehicle is nonlinear plant; it is difficult to obtain stable control for MAV attitude due to uncertainties. The purpose of this paper is to propose one robust stable control strategy for MAV to accommodate system uncertainties, variations, and external disturbances. Design/methodology/approach – First, by employing interval type-II fuzzy neural network (ITIIFNN) to approximate the nonlinearity function and uncertainty functions in the attitude angle dynamic model of micro aircraft vehicle (MAV). Then, the Lyapunov stability theorem is used to testify the asymptotic stability of the closed-loop system, the parameters of the ITIIFNN and gain of sliding mode control can be tuned on-line by adaptive laws based on Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system. Findings – The validity of the proposed control method has been verified through real-time experiments. The experimental results show that the performance of interval type-II fuzzy neural network based gain adaptive sliding mode controller (GASMC-ITIIFNN) is significantly improved compared with conventional adaptive sliding mode controller (CASMC), type-I fuzzy neural network based sliding mode controller (GASMC-TIFNN). Practical implications – This approach has been used in one MAV, the controller works well, and which could guarantee the MAV control system with good performances under uncertainties, variations, and external disturbances. Originality/value – The main original contributions of this paper are: the proposed control scheme makes full use of the nominal model of the MAV attitude control model; the overall closed-loop control system is globally stable demonstrated by Lyapunov stable theory; the tracking error can be asymptotically attenuated to a desired small level around zero by appropriate chosen parameters and learning rates; and the MAV attitude control system based on GASMC-ITIIFNN controller can achieve favourable tracking performance than GASMC-TIFNN and CASMC.

scholarly journals Performance of 2- Link Robot by utilizing Adaptive Sliding Mode Controller

2020 ◽  
Vol 26 (12) ◽  
pp. 44-65
Author(s):  
Dena Hameed Tu'ma ◽  
Ahmed Khalaf Hamoudi
Keyword(s):  
Sliding Mode ◽  
External Disturbance ◽  
Equations Of Motion ◽  
Systems Design ◽  
Sliding Mode Controller ◽  
Robot System ◽  
Adaptive Sliding Mode ◽  
Adaptive Sliding Mode Controller ◽  
Robot Performance ◽  
Better Than

The Sliding Mode Control (SMC) has been among powerful control techniques increasingly. Much attention is paid to both theoretical and practical aspects of disciplines due to their distinctive characteristics such as insensitivity to bounded matched uncertainties, reduction of the order of sliding equations of motion, decoupling mechanical systems design. In the current study, two-link robot performance in the Classical SMC is enhanced via Adaptive Sliding Mode Controller (ASMC) despite uncertainty, external disturbance, and coulomb friction. The key idea is abstracted as follows: switching gains are depressed to the low allowable values, resulting in decreased chattering motion and control's efforts of the two-link robot system. Un-known uncertainty bounded and reducing switching gains can be considered major advantages of ASMC leading to outperform ASMC upon CSMC. Simulink MATLAB 2019a was used to obtain the simulation outcomes. The outcomes have shown that both methodologies had good tracking performance to the desired position and made the system asymptotically stable through the steady-state errors investigate approaching zero. ASMC is better than CSMC illustrated by minimizing gains values, control efforts, and chattering for each link.

scholarly journals Adaptive Sliding Mode Controller Design For Attitude Small UAV

2015 ◽  
Vol 4 (3) ◽  
pp. 219
Author(s):  
Samaneh Amini
Keyword(s):  
Attitude Control ◽  
Controller Design ◽  
Sliding Mode ◽  
External Disturbance ◽  
Sliding Mode Controller ◽  
Attitude Control System ◽  
Strongly Coupled ◽  
Adaptive Sliding Mode ◽  
Adaptive Sliding Mode Controller ◽  
Aerial Vehicle

The dynamic of Unmanned Aerial Vehicle (UAV) is nonlinear, strongly coupled, multi-input multi-output (MIMO), and subject to uncertainties and external disturbances.  In this paper, an adaptive sliding mode controller (ASMC) is integrated to design the attitude control system for an inner loop fixed wing UAV. In the proposed scheme, sliding mode control law parameters due to uncertainty are assumed to be unknown and are estimated via adaptation laws. The synthesis of the adaptation laws is based on the positivity and Lyapunov design principle. Navigation outer loop parameters are regulated via PID controllers. Simulation results indicate that the proposed controller design can stabilize the nonlinear system, and it is robust to parametric model uncertainties and external disturbance.

Sign in / Sign up

Export Citation Format

Share Document