Super twisting sliding mode control algorithm for developing artificial pancreas in type 1 diabetes patients

2017 ◽  
Vol 38 ◽  
pp. 200-211 ◽  
Author(s):  
Sayyar Ahmad ◽  
NasimUllah ◽  
Nisar Ahmed ◽  
Muhammad Ilyas ◽  
Waqas Khan
Keyword(s):  
Type 1 Diabetes ◽  
Sliding Mode Control ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Artificial Pancreas ◽  
Mode Control ◽  
Diabetes Patients

A sliding mode control approach for patients with type 1 diabetes

2017 ◽  
Author(s):  
Eduardo Alvaro ◽  
Sebastian Rivadeneira ◽  
Danilo Chavez ◽  
Oscar Camacho ◽  
Pablo S. Rivadeneira
Keyword(s):  
Type 1 Diabetes ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Control Approach ◽  
Mode Control

Design of Intelligent Controller for Ship Motion with Input Saturation Based on Optimized Radial Basis Function Neural Network

2020 ◽  
Vol 13 ◽  
Author(s):  
Renqiang Wang ◽  
Qinrong Li ◽  
Shengze Miao ◽  
Keyin Miao ◽  
Hua Deng
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Sliding Mode Control ◽  
Intelligent Control ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Rbf Neural Network ◽  
Input Saturation ◽  
Ship Motion ◽  
Mode Control

Abstract: The purpose of this paper was to design an intelligent controller of ship motion based on sliding mode control with a Radial Basis Function (RBF) neural network optimized by the genetic algorithm and expansion observer. First, the improved genetic algorithm based on the distributed genetic algorithm with adaptive fitness and adaptive mutation was used to automatically optimize the RBF neural network. Then, with the compensation designed by the RBF neural network, anti-saturation control was realized. Additionally, the intelligent control algorithm was introduced by Sliding Mode Control (SMC) with the stability theory. A comparative study of sliding mode control integrated with the RBF neural network and proportional–integral–derivative control combined with the fuzzy optimization model showed that the stabilization time of the intelligent control system was 43.75% faster and the average overshoot was reduced by 52% compared with the previous two attempts. Background: It was known that the Proportional-Integral-Derivative (PID) control and self-adaptation control cannot really solve the problems of frequent disturbance from external wind and waves, as well as the problems with ship nonlinearity and input saturation. So, the previous ship motion controller should be transformed by advanced intelligent technology, on the basis of referring to the latest relevant patent design methods. Objective: An intelligent controller of ship motion was designed based on optimized Radial Basis Function Neural Network (RBFNN) in the presence of non-linearity, uncertainty, and limited input. Methods: The previous ship motion controller was remodeled based on Sliding Mode Control (SMC) with RBFNN optimized by improved genetic algorithm and expansion observer. The intelligent control algorithm integrated with genetic neural network solved the problem of system model uncertainty, limited control input, and external interference. Distributed genetic with adaptive fitness and adaptive mutation method guaranteed the adequacy of search and the global optimal convergence results, which enhanced the approximation ability of RBFNN. With the compensation designed by the optimized RBFNN, it was realized anti-saturation control. The chattering caused by external disturbance in SMC controller was reduced by the expansion observer. Results: A comparative study with RBFNN-SMC control and fuzzy-PID control, the stabilization time of the intelligent control system was 43.75% faster, the average overshoot was reduced by 52%, compared to the previous two attempts. Conclusion: The intelligent control algorithm succeed in dealing with the problems of nonlinearity, uncertainty, input saturation, and external interference. The intelligent control algorithm can be applied into research and development ship steering system, which would be created a new patent.

scholarly journals Research of Active Power Filter Modeling with Grid Impedance in Feedback Linearization and Quasi-Sliding Mode Control

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Zeyu Shi ◽  
Yingpin Wang ◽  
Yunxiang Xie ◽  
Lanfang Li ◽  
Xiaogang Xu
Keyword(s):  
Sliding Mode Control ◽  
Feedback Linearization ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Active Power Filter ◽  
Active Power ◽  
Pi Control ◽  
Power Filter ◽  
Mode Control ◽  
Grid Impedance

Active power filter (APF) is the most popular device in regulating power quality issues. Currently, most literatures ignored the impact of grid impedance and assumed the load voltage is ideal, which had not described the system accurately. In addition, the controllers applied PI control; thus it is hard to improve the compensation quality. This paper establishes a precise model which consists of APF, load, and grid impedance. The Bode diagram of traditional simplified model is obviously different with complete model, which means the descriptions of the system based on the traditional simplified model are inaccurate and incomplete. And then design exact feedback linearization and quasi-sliding mode control (FBL-QSMC) is based on precise model in inner current loop. The system performances in different parameters are analyzed and dynamic performance of proposed algorithm is compared with traditional PI control algorithm. At last, simulations are taken in three cases to verify the performance of proposed control algorithm. The results proved that the proposed feedback linearization and quasi-sliding mode control algorithm has fast response and robustness; the compensation performance is superior to PI control obviously, which also means the complete modeling and proposed control algorithm are correct.

scholarly journals Comparative simulation study on two estimation methods and two control strategies for semi-active suspension

2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110073
Author(s):  
Wang Xin ◽  
Gu Liang ◽  
Dong Mingming ◽  
Li Xiaolei
Keyword(s):  
Sliding Mode Control ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Structural Characteristics ◽  
Active Suspension ◽  
Road Surface ◽  
Estimation Methods ◽  
Vehicle Dynamic ◽  
Mode Control ◽  
Computational Overhead

With regard to the structural characteristics of the McPherson suspension system, when a vehicle is being driven on a rough road surface, the force direction of the suspension varies. This poses challenges to the vehicle’s driving safety and handling stability. Based on Lagrangian equations, this paper proposes a new nonlinear semi-vehicle suspension model and presents comparative studies, conducted through simulation, on the estimated accuracy and computational overhead of the small-computational-overhead extended Kalman filter (EKF) and unscented Kalman estimation (UKF) methods, and on the effectiveness of the skyhook sliding mode control (SHSMC) and nonlinear skyhook-sliding mode control (NSHSMC) semi-active suspension control methods. The response of the vehicle to the state estimation algorithm was evaluated through computer simulations using the Carsim vehicle dynamic software. The simulation results reveal that the vehicle dynamic states were satisfactorily estimated when the vehicle was driven on a rough road surface. Compared with the small-computational-overhead EKF algorithm, the estimated results of these variables based on the UKF algorithm have higher accuracy. However, the UKF algorithm requires longer computation time compared with the EKF algorithm. The SHSMC control algorithm achieved greater improvement for the vehicle’s drive handling stability in the 6–10-Hz vibration region compared with the NSHSMC control algorithm. In a high-frequency region over 10Hz, the semi-active suspension controlled by the SHSMC method had a more adverse effect on the driving comfort.

Terminal sliding mode control of permanent magnet synchronous motor based on the reaching law

2019 ◽  
Vol 234 (7) ◽  
pp. 849-859
Author(s):  
Peikun Zhu ◽  
Yong Chen ◽  
Meng Li
Keyword(s):  
Sliding Mode Control ◽  
Permanent Magnet ◽  
Parameter Uncertainty ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Terminal Sliding Mode ◽  
Reaching Law ◽  
Mode Control

Aiming at the parameter uncertainty and load torque disturbance of permanent magnet synchronous motor system, a terminal sliding mode control algorithm for permanent magnet synchronous motor based on the reaching law is proposed. First, a sliding mode control algorithm for sliding mode reaching law is proposed, which can dynamically adapt to the changes in system state. Second, a sliding mode disturbance observer is designed to estimate the lumped disturbance in real time and to compensate the controller for disturbance. On this basis, an online identification method based on disturbance observer for viscous friction coefficient and moment of inertia is used to reduce the influence of parameter uncertainty on the control system. Simulation and experimental results show the effectiveness of the method.

Input-decoupled discrete-time sliding mode control algorithm for servo multi-field multi-armature DC machine

2021 ◽  
Author(s):  
M.R. Homaeinezhad ◽  
M. Homaeinezhad ◽  
S. Akbari ◽  
D. Nayeb G.H. Hosseini
Keyword(s):  
Sliding Mode Control ◽  
Discrete Time ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Mode Control
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