A practical design sliding mode controller for DC–DC converter based on control parameters optimization using assigned poles associate to genetic algorithm

2013 ◽  
Vol 53 ◽  
pp. 761-773 ◽  
Author(s):  
M. Bensaada ◽  
A. Boudghene Stambouli
Keyword(s):  
Genetic Algorithm ◽  
Sliding Mode ◽  
Parameters Optimization ◽  
Sliding Mode Controller ◽  
Control Parameters ◽  
Practical Design

scholarly journals Pareto Design of Decoupled Sliding-Mode Controllers for Nonlinear Systems Based on a Multiobjective Genetic Algorithm

2012 ◽  
Vol 2012 ◽  
pp. 1-22 ◽  
Author(s):  
M. J. Mahmoodabadi ◽  
A. Bagheri ◽  
N. Nariman-zadeh ◽  
A. Jamali ◽  
R. Abedzadeh Maafi
Keyword(s):  
Genetic Algorithm ◽  
Nonlinear Systems ◽  
Fourth Order ◽  
Inverted Pendulum ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Objective Functions ◽  
Software Environment ◽  
Multiobjective Genetic Algorithm ◽  
Sliding Mode Controllers

This paper presents Pareto design of decoupled sliding-mode controllers based on a multiobjective genetic algorithm for several fourth-order coupled nonlinear systems. In order to achieve an optimum controller, at first, the decoupled sliding mode controller is applied to stablize the fourth-order coupled nonlinear systems at the equilibrium point. Then, the multiobjective genetic algorithm is applied to search the optimal coefficients of the decoupled sliding-mode control to improve the performance of the control system. Considered objective functions are the angle and distance errors. Finally, the simulation results implemented in the MATLAB software environment are presented for the inverted pendulum, ball and beam, and seesaw systems to assure the effectiveness of this technique.

Design of higher-order sliding mode controller based on genetic algorithm for a cooperative robotic system

2019 ◽  
Vol 8 (1) ◽  
pp. 269-277 ◽  
Author(s):  
Maryam Farahmandrad ◽  
Soheil Ganjefar ◽  
Heidar Ali Talebi ◽  
Mahdi Bayati
Keyword(s):  
Genetic Algorithm ◽  
Sliding Mode ◽  
Higher Order ◽  
Robotic System ◽  
Sliding Mode Controller

Sliding Mode Control of the Human Vestibular System

2012 ◽  
Author(s):  
Rachael McCarty ◽  
S. Nima Mahmoodi ◽  
Keith Williams
Keyword(s):  
Mathematical Model ◽  
Sliding Mode Control ◽  
Vestibular System ◽  
Head Movement ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Control Parameters ◽  
Mode Control ◽  
The Mathematical Model ◽  
The Brain

An original sliding mode controller is designed, based on an existing mathematical model for response control of the human vestibular system. The human vestibular system is located in the inner ear and significantly contributes to the functions of detecting head motion, maintaining balance and posture, and realizing gaze stabilization. The vestibular system sends signals to the brain to tell it how the head and body are moving, and the brain reacts by changing eye position accordingly. The nonlinearities of the vestibular system are not completely understood. The biggest nonlinearity is the nystagmus, a bouncing of the eyes to compensate for quick head movement. Another nonlinearity is that the quick phase does not start until head movement reaches a certain frequency. Considering these nonlinearities as well as the uncertainties of the system, sliding mode control a good choice for controlling the system. Several mathematical models of the human vestibular system are considered for use in the control design. The best model of those considered is chosen based on the models’ consideration of nonlinearities and their levels of complexity. The mathematical model used in this paper is a nonlinear transfer function. The output is controlled with a robust sliding mode controller. Results demonstrate the need to increase control parameters as frequency of the sinusoidal input increases to minimize overshoot error. However, since the human head cannot tolerate an infinitely large frequency input, control parameters also will necessarily be limited. Therefore, results show that the designed sliding mode robust controller is an effective mechanism for controlling the mathematical model of the human vestibular system.

Fuzzy Sliding Mode Controller for a Flexible Single-Link Robotic Manipulator

2005 ◽  
Vol 11 (2) ◽  
pp. 295-314 ◽  
Author(s):  
B. A. Bazzi ◽  
N. G. Chalhoub
Keyword(s):  
Fuzzy Inference ◽  
Sliding Mode ◽  
Angular Displacement ◽  
Robotic Manipulator ◽  
Sliding Mode Controller ◽  
Control Parameters ◽  
Single Link ◽  
Structural Deformations ◽  
Fuzzy Sliding Mode ◽  
Inference Systems

Two robust non-linear controllers have been developed in this study to control the rigid and flexible motions of a single-link robotic manipulator. The controllers consist of a conventional sliding mode controller (CSMC) and a fuzzy sliding mode controller (FSMC). The effects of fuzzy-tuning some of the CSMC control parameters on the overall performance of the arm have been investigated in this study. Furthermore, the proposed FSMC, whose parameters are determined by fuzzy inference systems, has been designed herein based on two Lyapunov functions. The rationale is to considerably reduce the momentum of the system before entering the boundary layer neighboring the sliding surface. This will significantly attenuate the structural deformations of the arm. The digital simulations have demonstrated that the structural deformations, incurred by the beam at the onset of its movement, can be significantly reduced by fuzzy-tuning some of the control parameters. Furthermore, the results have illustrated the superiority of the FSMC over the CSMC in producing a less oscillatory and more accurate response of the angular displacement at the base joint, in damping out the unwanted vibrations of the beam, and in requiring significantly smaller control torques.

scholarly journals Synchronization between Fractional-Order and Integer-Order Hyperchaotic Systems via Sliding Mode Controller

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Yan-Ping Wu ◽  
Guo-Dong Wang
Keyword(s):  
Theoretical Analysis ◽  
Fractional Order ◽  
Chaotic System ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Control Parameters ◽  
Chen System ◽  
Integer Order ◽  
Response Systems ◽  
Hyperchaotic Systems

The synchronization between fractional-order hyperchaotic systems and integer-order hyperchaotic systems via sliding mode controller is investigated. By designing an active sliding mode controller and choosing proper control parameters, the drive and response systems are synchronized. Synchronization between the fractional-order Chen chaotic system and the integer-order Chen chaotic system and between integer-order hyperchaotic Chen system and fractional-order hyperchaotic Rössler system is used to illustrate the effectiveness of the proposed synchronization approach. Numerical simulations coincide with the theoretical analysis.

Design of adaptive sliding mode controller applied to ultrasonic motor

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gangfeng Yan
Keyword(s):  
Sliding Mode Control ◽  
Control Method ◽  
Sliding Mode ◽  
Tracking Error ◽  
Adaptive Sliding Mode Control ◽  
Sliding Mode Controller ◽  
Control Parameters ◽  
Content Type ◽  
Adaptive Sliding Mode ◽  
Mode Control

Purpose The purpose of this paper is to achieve high-precision sliding mode control without chattering; the control parameters are easy to adjust, and the entire controller is easy to use in engineering practice. Design/methodology/approach Using double sliding mode surfaces, the gain of the control signal can be adjusted adaptively according to the error signal. A kind of sliding mode controller without chattering is designed and applied to the control of ultrasonic motors. Findings The results show that for a position signal with a tracking amplitude of 35 mm, the traditional sliding mode control method has a maximum tracking error of 0.3326 mm under the premise of small chattering; the boundary layer sliding mode control method has a maximum tracking error of 0.3927 mm without chattering, and the maximum tracking error of continuous switching adaptive sliding mode control is 0.1589 mm, and there is no chattering. Under the same control parameters, after adding a load of 0.5 kg, the maximum tracking errors of the traditional sliding mode control method, the boundary layer sliding mode control method and the continuous switching adaptive sliding mode control are 0.4292 mm, 0.5111 mm and 0.1848 mm, respectively. Originality/value The proposed method not only switches continuously, but also the amplitude of the switching signal is adaptive, while maintaining the robustness of the conventional sliding mode control method, which has strong engineering application value.

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