scholarly journals Robust Sliding Control of SEIR Epidemic Models

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Asier Ibeas ◽  
Manuel de la Sen ◽  
Santiago Alonso-Quesada
Keyword(s):  
Sliding Mode Control ◽  
Closed Loop ◽  
Sliding Mode ◽  
A Priori ◽  
Vaccination Strategy ◽  
Loop System ◽  
Theoretic Approach ◽  
Closed Loop System ◽  
Sliding Control ◽  
Mode Control

This paper is aimed at designing a robust vaccination strategy capable of eradicating an infectious disease from a population regardless of the potential uncertainty in the parameters defining the disease. For this purpose, a control theoretic approach based on a sliding-mode control law is used. Initially, the controller is designed assuming certain knowledge of an upper-bound of the uncertainty signal. Afterwards, this condition is removed while an adaptive sliding control system is designed. The closed-loop properties are proved mathematically in the nonadaptive and adaptive cases. Furthermore, the usual sign function appearing in the sliding-mode control is substituted by the saturation function in order to prevent chattering. In addition, the properties achieved by the closed-loop system under this variation are also stated and proved analytically. The closed-loop system is able to attain the control objective regardless of the parametric uncertainties of the model and the lack ofa prioriknowledge on the system.

Adaptive neural sliding mode control with prescribed performance of robotic manipulators subject to backlash hysteresis

2021 ◽  
pp. 095440622110145
Author(s):  
Huaizhen Wang ◽  
Lijin Fang ◽  
Junyi Wang ◽  
Tangzhong Song ◽  
Hesong Shen
Keyword(s):  
Sliding Mode Control ◽  
Closed Loop ◽  
Sliding Mode ◽  
Nonlinear Function ◽  
Robotic Manipulators ◽  
Loop System ◽  
Closed Loop System ◽  
Terminal Sliding Mode ◽  
Prescribed Performance ◽  
Mode Control

Robust and precise control of robot systems are still challenging problems due to the existence of uncertainties and backlash hysteresis. To deal with the problems, an adaptive neural sliding mode control with prescribed performance is proposed for robotic manipulators. A finite-time nonsingular terminal sliding mode control combined with a new prescribed performance function (PPF) is developed to guarantee the transient and steady-state performance of the closed-loop system. Based on the sliding mode variable, an adaptive law is presented to effectively estimate the bound of system uncertainties where the prior knowledge of uncertainties is not needed. To approximate nonlinear function and unknown dynamics, the Gaussian radial basis function neural networks(RBFNNs) is introduced to compensate the lumped nonlinearities. All signals of the closed-loop system are proven to be uniformly ultimately bounded (UUB) by Lyapunov analysis. Finally, comparative simulations are conducted to illustrate superiority and reliability of the proposed control strategy.

scholarly journals Adaptive Sliding Mode Control of Mobile Manipulators with Markovian Switching Joints

2012 ◽  
Vol 2012 ◽  
pp. 1-24 ◽  
Author(s):  
Liang Ding ◽  
Haibo Gao ◽  
Kerui Xia ◽  
Zhen Liu ◽  
Jianguo Tao ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Closed Loop ◽  
Sliding Mode ◽  
Loop System ◽  
Markovian Switching ◽  
Adaptive Sliding Mode Control ◽  
Mobile Manipulators ◽  
Closed Loop System ◽  
Mode Control ◽  
Hybrid Joints

The hybrid joints of manipulators can be switched to either active (actuated) or passive (underactuated) mode as needed. Consider the property of hybrid joints, the system switches stochastically between active and passive systems, and the dynamics of the jump system cannot stay on each trajectory errors region of subsystems forever; therefore, it is difficult to determine whether the closed-loop system is stochastically stable. In this paper, we consider stochastic stability and sliding mode control for mobile manipulators using stochastic jumps switching joints. Adaptive parameter techniques are adopted to cope with the effect of Markovian switching and nonlinear dynamics uncertainty and follow the desired trajectory for wheeled mobile manipulators. The resulting closed-loop system is bounded in probability and the effect due to the external disturbance on the tracking errors can be attenuated to any preassigned level. It has been shown that the adaptive control problem for the Markovian jump nonlinear systems is solvable if a set of coupled linear matrix inequalities (LMIs) have solutions. Finally, a numerical example is given to show the potential of the proposed techniques.

Optimal Sliding Mode Control for a Class of Underactuated Nonlinear Systems

2011 ◽  
Author(s):  
Parham Ghorbanian ◽  
Sergey G. Nersesov ◽  
Hashem Ashrafiuon
Keyword(s):  
Nonlinear Systems ◽  
Sliding Mode Control ◽  
Closed Loop ◽  
Sliding Mode ◽  
Sufficient Conditions ◽  
Domain Of Attraction ◽  
Loop System ◽  
Closed Loop System ◽  
Sliding Surfaces ◽  
Mode Control

In this paper, a general framework that provides sufficient conditions for asymptotic stabilization of underactuated nonlinear systems using an optimal sliding mode control in the presence of system uncertainties is presented. A performance objective is used to optimally select the parameters of the sliding mode control surfaces subject to state and input constraints. It is shown that the closed-loop system trajectories reach the optimal sliding surfaces in finite time and a constructive methodology to determine exponential stability of the closed-loop system on the sliding surfaces is developed which ensures asymptotic stability of the overall closed-loop system. The framework further provides the basis to determine an estimate of the domain of attraction for the closed-loop system with uncertainties. The results developed in this work are experimentally validated using a linear inverted pendulum testbed which show a good match between the actual domain of attraction of the upward equilibrium state and its analytical estimate.

Sliding Mode Control of a 2D Torsional MEMS Micromirror with Sidewall Electrodes

2013 ◽  
Vol 3 (1) ◽  
pp. 16-26
Author(s):  
Hui Chen ◽  
Manu Pallapa ◽  
Weijie Sun ◽  
Zhendong Sun ◽  
John T. W. Yeow
Keyword(s):  
Sliding Mode Control ◽  
Closed Loop ◽  
Sliding Mode ◽  
Loop System ◽  
Closed Loop System ◽  
Parameter Uncertainties ◽  
External Disturbances ◽  
Mode Control ◽  
Control Scheme ◽  
The Stability

This paper presents a sliding mode control scheme to improve the positioning performance of a 2-Degree-of-freedom (DOF) torsional MEMS micromirror with sidewall electrodes. The stability of closed-loop system is proved by Lyapunov stability theorem under the existence of bounded parameter uncertainties and external disturbances. Furthermore, the performance of the closed-loop system is illustrated by experimental and simulation results which verify that the feasibility and effectiveness of the proposed scheme. The results demonstrated that the torsional MEMS micromirror with the proposed sliding mode controller has a good transient response and tracking performance.

Adaptive funnel fast nonsingular terminal sliding mode control for robotic manipulators with dynamic uncertainties

2020 ◽  
pp. 095440622097826
Author(s):  
Huaizhen Wang ◽  
Lijin Fang ◽  
Menghui Hu ◽  
Tangzhong Song ◽  
Jiqian Xu
Keyword(s):  
Sliding Mode Control ◽  
Closed Loop ◽  
Sliding Mode ◽  
Robotic Manipulators ◽  
Loop System ◽  
Terminal Sliding Mode Control ◽  
Closed Loop System ◽  
Terminal Sliding Mode ◽  
Mode Control ◽  
Nonsingular Terminal Sliding Mode

In this paper, a novel adaptive funnel fast nonsingular terminal sliding mode control for robotic manipulators with dynamic uncertainties is proposed. A modified funnel variable is utilized to transform the tracking error fall within funnel boundary, which improves the transient and steady-state tracking performance of robotic manipulators. Based on the transformed error, a novel funnel fast nonsingular terminal sliding mode surface is developed and a sliding mode control law is designed to stabilize the closed-loop system and achieve high tracking precision. An adaptive update law combined with the sliding mode surface is designed to deal with uncertainties and external disturbances where their upper bounds are unknown in practical cases. The stability and finite time convergence of the closed-loop system are proved by Lyapunov stability theorem. Simulation results and discussions are presented to demonstrate the effectiveness and high-precision tracking control for robotic manipulators.

scholarly journals Fractional-Order Sliding Mode Control of Overhead Cranes   

2020 ◽  
Vol 31 (1) ◽  
pp. 68-76
Keyword(s):  
Sliding Mode Control ◽  
Fractional Order ◽  
Closed Loop ◽  
Control Structure ◽  
Adaptive System ◽  
Sliding Mode ◽  
Lyapunov Theory ◽  
Closed Loop System ◽  
Control Approach ◽  
Mode Control

We constitute a control system for overhead crane with simultaneous motion of trolley and payload hoist to destinations and suppression of payload swing. Controller core made by sliding mode control (SMC) assures the robustness. This control structure is inflexible since using fixed gains. For overcoming this weakness, we integrate variable fractional-order derivative into SMC that leads to an adaptive system with adjustable parameters. We use Mittag–Leffler stability, an enhanced version of Lyapunov theory, to analyze the convergence of closed-loop system. Applying the controller to a practical crane shows the efficiency of proposed control approach. The controller works well and keeps the output responses consistent despite the large variation of crane parameters.

Observer-based sliding mode control for piezoelectric wing bending-torsion coupling flutter involving delayed output

2020 ◽  
pp. 107754632094912
Author(s):  
Da Li ◽  
Hui Yang ◽  
Na Qi ◽  
Jiaxin Yuan
Keyword(s):  
Time Delay ◽  
Sliding Mode Control ◽  
Linear Matrix Inequalities ◽  
Closed Loop ◽  
Sliding Mode ◽  
Loop System ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Closed Loop System ◽  
Piezoelectric Patch

An observer-based sliding mode control scheme is proposed for suppressing bending-torsion coupling flutter motions of a wing aeroelastic system with delayed output by using the piezoelectric patch actuators. The wing structure is modeled as a thin-walled beam, and the aerodynamics on the wing are computed by the strip theory. For the implementation of the control algorithm, the piezoelectric patch is bonded on the top surface of the beam to act as the actuator. Ignoring the effect of piezoelectric actuators on structural dynamics, only considering the bending moments induced by piezoelectric effects, the corresponding dynamic motion equation is established by using the Lagrange method with the assumed mode method. The flutter speed and frequency of the closed-loop system with time delay are obtained by solving a polynomial eigenvalue problem. An observer-based controller that does not dependent on time delay is developed for suppressing the flutter, and the corresponding gain matrices are obtained by solving linear matrix inequalities. The sufficient condition for the asymptotic stability of the closed-loop system is derived in terms of linear matrix inequalities. The simulation results demonstrate that the proposed control strategy based on the piezoelectric actuator is effective in wing bending-torsion coupling flutter system with a delayed output.

Mixed H∞ and passive projective synchronization for fractional-order memristor-based neural networks with time delays via adaptive sliding mode control

2017 ◽  
Vol 31 (14) ◽  
pp. 1750160 ◽  
Author(s):  
Shuai Song ◽  
Xiaona Song ◽  
Ines Tejado Balsera
Keyword(s):  
Neural Networks ◽  
Sliding Mode Control ◽  
Fractional Order ◽  
Time Delays ◽  
Closed Loop ◽  
Sliding Mode ◽  
Projective Synchronization ◽  
Adaptive Sliding Mode Control ◽  
Closed Loop System ◽  
Mode Control

This paper investigates the mixed [Formula: see text] and passive projective synchronization problem for fractional-order (FO) memristor-based neural networks with time delays. Our aim is to design a controller such that, though the unavoidable phenomena of time delay and external disturbances is fully considered, the resulting closed-loop system is stable with a mixed [Formula: see text] and passive performance level. By combining sliding mode control and adaptive control methods, a novel adaptive sliding mode control strategy is designed for the synchronization of time-delayed FO dynamic networks. Via the application of FO system stability theory, the projective synchronization conditions are addressed in terms of linear matrix inequalities. Based on the conditions, a desired controller which can guarantee the stability of the closed-loop system and also ensure a mixed [Formula: see text] and passive performance level is designed. Finally, two simulation examples are given to illustrate the effectiveness of the proposed method.

Synchronization of Chaotic Gyro Systems via Sliding Mode Control with Cooperative Weights Neural Network

2013 ◽  
Vol 427-429 ◽  
pp. 1101-1104
Author(s):  
Yan Qiu Che ◽  
Ting Ting Yang ◽  
Xiao Qin Li ◽  
Rui Xue Li
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Closed Loop ◽  
Control Method ◽  
Sliding Mode ◽  
Closed Loop System ◽  
External Disturbances ◽  
Mode Control ◽  
Nonlinear Uncertainties ◽  
Stability Method

In this paper, a sliding mode control (SMC) with a cooperative weights neural network (CWNN) is proposed to realize the synchronization of two chaotic Gyro systems with nonlinear uncertainties and external disturbances. By the Lyapunov stability method, the overall closed-loop system is shown to be stable and chaos synchronizationis obtained. The simulation results demonstrate the effectiveness of the proposed control method.

Sign in / Sign up

Export Citation Format

Share Document