On-line genetic algorithm-based fuzzy-neural sliding mode controller using improved adaptive bound reduced-form genetic algorithm

2009 ◽  
Vol 40 (6) ◽  
pp. 571-585 ◽  
Author(s):  
Ping-Zong Lin ◽  
Wei-Yen Wang ◽  
Tsu-Tian Lee ◽  
Chi-Hsu Wang
Keyword(s):  
Genetic Algorithm ◽  
Sliding Mode ◽  
Reduced Form ◽  
Sliding Mode Controller ◽  
Fuzzy Neural ◽  
On Line

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

scholarly journals Nonlinear PD plus sliding mode control with application to a parallel delta robot

2018 ◽  
Vol 69 (5) ◽  
pp. 329-336 ◽  
Author(s):  
Chems Eddine Boudjedir ◽  
Djamel Boukhetala ◽  
Mohamed Bouri
Keyword(s):  
Convergence Rate ◽  
Error Rate ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Tracking Error ◽  
Sliding Mode Controller ◽  
External Disturbances ◽  
On Line ◽  
Delta Robot ◽  
The Stability

Abstract In this paper, a hybrid nonlinear proportional-derivative-sliding mode controller (NPD-SMC) is developed for the trajectory tracking of robot manipulators. The proposed controller combines the advantage of the easy implementation of NPD control and the robustness of SMC. The gains of PD control are tuned on-line in order to increase the convergence rate, whereas the SMC term is introduced to reject the external disturbances without requiring to know the system dynamics. The stability of the NPD-SMC is proved using Lyaponuv theorem, and it is demonstrated that the tracking error and the tracking error rate converge asymptotically to zero. Experiments are carried out on the parallel Delta robot to illustrate the effectiveness and robustness of the proposed approach. It is also shown the superiority of the NPD-SMC control over the NPD control and PD-SMC control.

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