Global back—Stepping adaptive sliding mode control of naval gun servo system with backlash

Author:

Jiang Shang1ORCID,Sun Dongyan1,Liu Yan1,Yang Yue1,Wu Xiaolong2,Wang Yuxin3

Affiliation:

1. Dalian Naval Academy 1 , Dalian 116018, China

2. 92118 Unit of People’s Liberation Army 2 , Zhoushan 316000, China

3. 91999 Unit of People’s Liberation Army 3 , Qingdao 266000, China

Abstract

A compensation approach for global back-stepping adaptive sliding mode control to deal with the nonlinear backlash in naval gun servo systems has been proposed in this paper. First, by introducing an approximate dead-zone model into the double inertia system and considering the nonlinear disturbances during the firing at level 5 sea conditions, the state space model of the system is established, which is divided into three subsystems. Then, based on the back-stepping control theory, the Lyapunov function is constructed step-by-step using the recursive approach. By combining the sliding mode control in Step 3, the adaptive law of uncertain parameters is given, and the global back-stepping adaptive sliding mode controller is designed. In addition, the global stability of the closed-loop system is proved by Barbalat’s lemma. The simulation results show that, compared with proportional integral differential control, this approach can compensate the backlash more effectively, reduce the torsional oscillations in both the driving torque and load velocity, and ensure a higher position tracking accuracy and robustness of the system under the same operating conditions.

Funder

Research on Multi-Projectile Collaborative Attack and Flight Control Technology

Publisher

AIP Publishing

Reference21 articles.

1. Backlash compensation method in naval gun servo system based on global back-stepping sliding mode control;J. Nav. Univ. Eng.,2018

2. Terminal sliding mode control for mechatronic servo systems with backlash nonlinearity compensation;Trans. China Electrotech. Soc.,2016

3. Cooperative neuro adaptive control of leader following uncertain multi-agent systems with unknown hysteresis and dead-zone;J. Syst. Sci. Complexity,2020

4. Neural network synchronization of fractional-order chaotic systems subject to backlash nonlinearity;AIP Adv.,2020

5. Modified dynamic surface approach with bias torque for multi-motor servomechanism;Control Eng. Pract.,2016

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