Feedforward Smith predictor sliding mode control algorithm for a class of first order system with integrator and time delay

2011 ◽  
Author(s):  
Chuanxiu Li ◽  
Dongya Zhao ◽  
Tao Zou ◽  
Xianxia Zhang
Keyword(s):  
Time Delay ◽  
Sliding Mode Control ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Smith Predictor ◽  
Order System ◽  
First Order ◽  
Mode Control

scholarly journals Adaptive Output Feedback Sliding Mode Control for Complex Interconnected Time-Delay Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-15
Author(s):  
Van Van Huynh ◽  
Yao-Wen Tsai ◽  
Phan Van Duc
Keyword(s):  
Time Delay ◽  
Sliding Mode Control ◽  
Output Feedback ◽  
Sliding Mode ◽  
Sufficient Conditions ◽  
Delay Systems ◽  
Order System ◽  
Linear Matrix ◽  
Time Delay Systems ◽  
Mode Control

We extend the decentralized output feedback sliding mode control (SMC) scheme to stabilize a class of complex interconnected time-delay systems. First, sufficient conditions in terms of linear matrix inequalities are derived such that the equivalent reduced-order system in the sliding mode is asymptotically stable. Second, based on a new lemma, a decentralized adaptive sliding mode controller is designed to guarantee the finite time reachability of the system states by using output feedback only. The advantage of the proposed method is that two major assumptions, which are required in most existing SMC approaches, are both released. These assumptions are (1) disturbances are bounded by a known function of outputs and (2) the sliding matrix satisfies a matrix equation that guarantees the sliding mode. Finally, a numerical example is used to demonstrate the efficacy of the method.

Time-Delay Sliding Mode Control for a Servo

1999 ◽  
Vol 121 (1) ◽  
pp. 143-148 ◽  
Author(s):  
Jong Hyeon Park ◽  
You Moo Kim
Keyword(s):  
Time Delay ◽  
Sliding Mode Control ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Stick Slip ◽  
Mode Control ◽  
Model Control ◽  
Delay Control ◽  
Series Of Experiments ◽  
Nominal Performance

In this paper, a new control algorithm called the time-delay sliding mode control (TDSMC), based on the time delay control (TDC) and the integral sliding mode control (SMC), is proposed and applied for controlling DC servos with a seal installed on their rotating axes. This algorithm adopts the robustness of sliding model control and improves the robustness of the TDC. The results of a series of experiments on a DC servo motor system with stick-slip friction show TDSMC is compatable with the TDC in the nominal performance, but is superior to the TDC and the PID control in the performance robustness. Settling time is used as a measure of the performance.

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 A Novel Adaptive Super-Twisting Sliding Mode Control Scheme with Time-Delay Estimation for a Single Ducted-Fan Unmanned Aerial Vehicle

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 54
Author(s):  
Minh-Thien Tran ◽  
Dong-Hun Lee ◽  
Soumayya Chakir ◽  
Young-Bok Kim
Keyword(s):  
Time Delay ◽  
Sliding Mode Control ◽  
Unmanned Aerial Vehicle ◽  
Sliding Mode ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Mode Control ◽  
Ducted Fan ◽  
Control Scheme ◽  
Aerial Vehicle

This article proposes a novel adaptive super-twisting sliding mode control scheme with a time-delay estimation technique (ASTSMC-TDE) to control the yaw angle of a single ducted-fan unmanned aerial vehicle system. Such systems are highly nonlinear; hence, the proposed control scheme is a combination of several control schemes; super-twisting sliding mode, TDE technique to estimate the nonlinear factors of the system, and an adaptive sliding mode. The tracking error of the ASTSMC-TDE is guaranteed to be uniformly ultimately bounded using Lyapunov stability theory. Moreover, to enhance the versatility and the practical feasibility of the proposed control scheme, a comparison study between the proposed controller and a proportional-integral-derivative controller (PID) is conducted. The comparison is achieved through two different scenarios: a normal mode and an abnormal mode. Simulation and experimental tests are carried out to provide an in-depth investigation of the performance of the proposed ASTSMC-TDE control system.

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.

Sign in / Sign up

Export Citation Format

Share Document