scholarly journals Extended State Observer-Based Sliding Mode Control with New Reaching Law for PMSM Speed Control

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Junzhang Qian ◽  
Ai Xiong ◽  
Wenli Ma

In order to improve the performance of external disturbance rejection of permanent magnet synchronous motor (PMSM) in speed control, sliding mode control with extended state observer is adopted in this paper. First, an exponential function-based sliding mode reaching law (ESMRL) is developed. The ESMRL can dynamically adapt to the variations of the controlled system, which decrease the reaching time in reaching stage and void chattering in sliding motion stage while maintaining high tracking accuracy of the servo system. Then, an extended state observer (ESO) is introduced to the controller to simultaneously estimate external disturbance and compensate the uncertainties. Simulation results demonstrate that the proposed method has better suppression of chattering effect and disturbance rejection ability while ensuring dynamic performance.

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Zhenlei CHEN ◽  
Qing GUO ◽  
Yao YAN ◽  
Dan JIANG

For the 2- Degree of Freedom (DOF) lower limb exoskeleton, to ensure the system robustness and dynamic performance, a linear-extended-state-observer-based (LESO) robust sliding mode control is proposed to not only reduce the influence of parametric uncertainties, unmodeled dynamics, and external disturbance but also estimate the unmeasurable real-time joint angular velocity directly. Then, via Lyapunov technology, the stability of the corresponding LESO and controller is proven. The appropriate and reasonable simulation was carried out to verify the effectiveness of the proposed LESO and exoskeleton controller.


Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5091
Author(s):  
Yongli Yan ◽  
Li Ding ◽  
Yana Yang ◽  
Fucai Liu

The goal of this paper is to improve the synchronization control performance of nonlinear teleoperation systems with system uncertainties in the presence of time delays. In view of the nonlinear discrete states of the teleoperation system in packet-switched communication networks, a new discrete sliding mode control (DSMC) strategy is performed via a new reaching law in task space. The new reaching law is designed to reduce the chattering and improve control performance. Moreover, an adaptive extended state observer (AESO) is used to estimate the total system disturbances. The additional gain of AESO is adjusted in time to decrease the estimation errors of both system states and disturbances automatically and improve the estimation performances of the AESO. Finally, the validity of the designed control strategy is demonstrated by both simulation and experiments. Furthermore, the experimental comparison results indicate that the improvement is achievable with the proposed AESO and DSMC.


2021 ◽  
Vol 18 (1) ◽  
pp. 172988142098603
Author(s):  
Daoxiong Gong ◽  
Mengyao Pei ◽  
Rui He ◽  
Jianjun Yu

Pneumatic artificial muscles (PAMs) are expected to play an important role in endowing the advanced robot with the compliant manipulation, which is very important for a robot to coexist and cooperate with humans. However, the strong nonlinear characteristics of PAMs hinder its wide application in robots, and therefore, advanced control algorithms are urgently needed for making the best use of the advantages and bypassing the disadvantages of PAMs. In this article, we propose a full-order sliding mode control extended state observer (fSMC-ESO) algorithm that combines the ESO and the fSMC for a robotic joint actuated by a pair of antagonistic PAMs. The fSMC is employed to eliminate the chattering and to guarantee the finite-time convergence, and the ESO is adopted to observe both the total disturbance and the states of the robot system, so that we can inhibit the disturbance and compensate the nonlinearity efficiently. Both simulations and physical experiments are conducted to validate the proposed method. We suggest that the proposed method can be applied to the robotic systems actuated by PAMs and remarkably improve the performance of the robot system.


2011 ◽  
Vol 19 (10) ◽  
pp. 2409-2418
Author(s):  
马晓军 MA Xiao-jun ◽  
袁东 YUAN Dong ◽  
李匡成 LI Kuang-cheng ◽  
魏曙光 WEI Shu-guang

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