scholarly journals Decoupled error dynamics design for discrete-time sliding mode control in industrial servo systems under control input saturation and disturbance

Mechatronics ◽  
2021 ◽  
Vol 77 ◽  
pp. 102581
Author(s):  
Ji-Seok Han ◽  
Tae-Ho Oh ◽  
Young-Seok Kim ◽  
Hyun-Taek Lim ◽  
Dae-Young Yang ◽  
...  
2019 ◽  
Vol 52 (15) ◽  
pp. 460-464 ◽  
Author(s):  
Ji-Seok Han ◽  
Tae-Il Kim ◽  
Tae-Ho Oh ◽  
Young-Seok Kim ◽  
Ji-Hyung Lee ◽  
...  

2006 ◽  
Vol 128 (3) ◽  
pp. 729-730
Author(s):  
Hanz Richter ◽  
Eduardo A. Misawa

A result that allows us to specify the sliding manifold in observer-based discrete-time sliding mode control is presented. Selection of coefficients is done by analyzing the tracking error dynamics inside the boundary layer, where the closed-loop system has a linear state feedback configuration, rather than assuming that ideal sliding occurs. The result facilitates assignment of eigenvalues for the system matrix which defines such linear dynamics.


Entropy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 271 ◽  
Author(s):  
Shaojie Wang ◽  
Amin Yousefpour ◽  
Abdullahi Yusuf ◽  
Hadi Jahanshahi ◽  
Raúl Alcaraz ◽  
...  

In this paper, dynamical behavior and synchronization of a non-equilibrium four-dimensional chaotic system are studied. The system only includes one constant term and has hidden attractors. Some dynamical features of the governing system, such as invariance and symmetry, the existence of attractors and dissipativity, chaotic flow with a plane of equilibria, and offset boosting of the chaotic attractor, are stated and discussed and a new disturbance-observer-based adaptive terminal sliding mode control (ATSMC) method with input saturation is proposed for the control and synchronization of the chaotic system. To deal with unexpected noises, an extended Kalman filter (EKF) is implemented along with the designed controller. Through the concept of Lyapunov stability, the proposed control technique guarantees the finite time convergence of the uncertain system in the presence of disturbances and control input limits. Furthermore, to decrease the chattering phenomena, a genetic algorithm is used to optimize the controller parameters. Finally, numerical simulations are presented to demonstrate the performance of the designed control scheme in the presence of noise, disturbances, and control input saturation.


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