An enhanced tracking control of marine surface vessels based on adaptive integral sliding mode control and disturbance observer

2019 ◽  
Vol 90 ◽  
pp. 30-40 ◽  
Author(s):  
Mien Van
2019 ◽  
Vol 16 (3) ◽  
pp. 172988141984412 ◽  
Author(s):  
Wei Yuan ◽  
Guoqin Gao

This article seeks to achieve high tracking performance of the hybrid automobile electro-coating conveying mechanism with disturbances and uncertainties. An integral sliding mode control scheme is first presented to eliminate the reaching phase in sliding mode control. Then, an adaptive integral sliding mode controller is designed without knowing the disturbance information. Finally, a composite strategy, referred to as nonlinear disturbance observer (NDO)-based adaptive integral sliding model control, is put forward to further reduce the switching gain. By compensating the lumped disturbances via a NDO, the switching gain is only required to be higher than upper bound of the disturbance estimation error which is much smaller than actual disturbance. The results of both numerical simulations and experiments show that the proposed approach has good control performance especially in reducing the switching gain and alleviating the chattering problem.


Author(s):  
Nor Mohd Haziq Norsahperi ◽  
Kumeresan A. Danapalasingam

This paper provides a systematic comparative study of position tracking control of nonlinear robotic manipulators. The main contribution of this study is a comprehensive numerical simulation assessing position tracking performances and energy consumption of integral sliding mode control (ISMC), a linear-quadratic regulator with integral action (LQRT ), and optimal integral sliding mode control (OISMC) under three conditions; namely, Case I) without the coupling effect, Case II) with the coupling effect on Link 1 only, and Case III) with the coupling effect on Link 2 only. The viability of the concept is evaluated based on three performance criteria, i.e., the step-response characteristics, position tracking error, and energy consumption of the aforementioned controllers. Based upon the simulation study, it has been found that OISMC offers performances almost similar to ISMC with more than 90% improvement of tracking performance under several cases compared to LQRT; however, energy consumption is successfully reduced by 3.6% in comparison to ISMC. Energy consumption of OISMC can be further reduced by applying optimization algorithms in tuning the weighting matrices. This paper can be considered significant as a robotic system with high tracking accuracy and low energy consumption is highly demanded to be implemented in smart factories, especially for autonomous systems.


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