scholarly journals Two-Degree-Of-Freedom Dynamic Model-Based Terminal Sliding Mode Control with Observer for Dual-Driving Feed Stage

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 488 ◽  
Author(s):  
Wei Fan ◽  
Hong Lu ◽  
Xinbao Zhang ◽  
Yongquan Zhang ◽  
Rong Zeng ◽  
...  

The position synchronous control of multi-axis gantry-type feed stage is crucial in precision machine tools. Industrial position control which aims to widen the bandwidth and improve disturbance rejection of single axis is not enough to achieve precise synchronization in a dual-driving feed stage. The characteristics diversity, transmission-mechanism deformation, and mechanical coupling effect between dual axes will degrade the control accuracy. Hence, the novel two-degree-of-freedom (2-DOF) dynamic model-based terminal sliding mode control (TSMC) with disturbance and state observer is proposed in this paper for the synchronous control of a 2-DOF dual-driving feed stage. The 2-DOF dynamic model, based on Lagrange equation, is established along with the parameters identification method. The predictive natural frequencies and vibration modes frequencies by the proposed dynamic model are compared by a modal experiment. Then, the 2-DOF dynamic model-based TSMC is provided to satisfy the tracking and synchronization control. In order to reduce the chattering and to increase the robustness against the mechanical coupling, the disturbance and state observer is designed. Moreover, Lyapunov stability criterion is used to analyze the stability of the proposed control scheme. Finally, an industrial application of 2-DOF dual-driving feed stage is utilized to validate the effectiveness of the proposed control scheme. The proposed 2-DOF dynamic model-based TSMC with observer has been effectively demonstrated to improve synchronous performance and tracking accuracy.

Author(s):  
Xiaoqian Yang ◽  
Jian Li ◽  
Yi Dong

A new control scheme for flexible air-breathing hypersonic vehicle is designed in this paper based on non-singular fast terminal sliding mode control and nonlinear disturbance observer. The proposed control scheme is derived from basic back-stepping method, which is capable of handling the higher-order nonlinear system, and a novel terminal sliding mode control method is designed for the last step to promise the finite time convergence and improve the steady-state precision. Meanwhile, a command filter is used to avoid the “explosion of complexity” in traditional back-stepping method. To overcome inevitable uncertainties as well as cross couplings between flexible and rigid modes, NDO is introduced to estimate diverse uncertainties. Thus flexible modes and uncertainties can be suppressed simultaneously. The convergence of overall closed-loop system states is proved via Lyapunov analysis. Numerical simulations show the effectiveness and advantages of the proposed control strategy.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yang Wang ◽  
Mingshu Chen ◽  
Yu Song

This paper concentrates on the predefined-time trajectory tracking for an uncertain robotic manipulator system. First, a modified predefined-time control (PTC) algorithm is proposed. Subsequently, with the help of proposed modified PTC algorithm and the nonsingular design method of terminal sliding mode, a novel nonsingular terminal sliding-mode control (NTSMC) scheme is proposed for ensuring the predefined-time convergence of tracking errors. The advantages of the newly proposed control scheme are as follows. (i) Unlike the conventional predefined-time sliding-mode control (SMC) which only guarantees the predefined-time convergence of sliding-mode surface, the proposed scheme can guarantee the predefined-time convergence of tracking errors. (ii) Compared with the conventional PTC algorithm, the proposed modified PTC algorithm can reduce the initial control peaking and enhance the precision of convergence time. The performance and effectiveness of the proposed control scheme are illustrated by comparing with the existing methods.


IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 5436-5444 ◽  
Author(s):  
Changfan Zhang ◽  
Zhenzhen Lin ◽  
Simon X. Yang ◽  
Jing He

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