Genetic Algorithm Tuned Super Twisted Sliding Mode Controller (STSMC) for Self-balancing Control of a Two-Wheel Electric Scooter

Author(s):  
Tefera T. Yetayew ◽  
Daniel G. Tesfaye
2012 ◽  
Vol 2012 ◽  
pp. 1-22 ◽  
Author(s):  
M. J. Mahmoodabadi ◽  
A. Bagheri ◽  
N. Nariman-zadeh ◽  
A. Jamali ◽  
R. Abedzadeh Maafi

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.


2019 ◽  
Vol 8 (1) ◽  
pp. 269-277 ◽  
Author(s):  
Maryam Farahmandrad ◽  
Soheil Ganjefar ◽  
Heidar Ali Talebi ◽  
Mahdi Bayati

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Van Dong Hai Nguyen ◽  
Xuan-Dung Huynh ◽  
Minh-Tam Nguyen ◽  
Ionel Cristian Vladu ◽  
Mircea Ivanescu

Dynamic equations and the control law for a class of robots with elastic underactuated MIMO system of legs, athlete Robot, are discussed in this paper. The dynamic equations are determined by Euler-Lagrange method. A new method based on hierarchical sliding mode for controlling postures is also introduced. Genetic algorithm is applied to design the oscillator for robot motion. Then, a hierarchical sliding mode controller is implemented to control basic posture of athlete robot stepping. Successful simulation results show the motion of athlete robot.


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