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Ship trajectory tracking control system design based on sliding mode control algorithm

100%

Liu Y. , Bu R. , Gao X.

2018

tom nr 3

26--34

The paper reports the design and tests of the planar autopilot navigation system in the three-degree-of-freedom (3-DOF) plane (surge, sway and yaw) for a ship. The aim of the tests was to check the improved maneuverability of the ship in open waters using the improved nonlinear control algorithm, developed based on the sliding mode control theory for the ship-trajectory tracking problem of under-actuated ships with static constraints, actuator saturation, and parametric uncertainties. With the integration of the simple increment feedback control law, the dynamic control strategy was developed to fulfill the under-actuated tracking and stabilization objectives. In addition, the LOS (line of sight) guidance system was applied to control the motion path, whereas the sliding mode controller was used to emulate the rudder angle and propeller rotational speed control. Firstly, simulation tests were performed to verify the validity of the basic model and the tracking control algorithm. Subsequently, full scale maneuverability tests were done with a novel container ship, equipped with trajectory tracking control and sliding mode controller algorithm, to check the dynamic stability performance of the ship. The results of the theoretical and numerical simulation on a training ship verify the invariability and excellent robustness of the proposed controller, which: effectively eliminates system chattering, solves the problem of lateral drift of the ship, and maintains the following of the trajectory while simultaneously achieving global stability and robustness.

Spatiotemporal variations of growing-season NDVI associated with climate change in northeastern China’s permafrost zone

75%

Gua J. , Hu Y. , Xiong Z. , Yan X. , Ren B. , Bu R.

nr 4

Vegetation is an essential component of terrestrial ecosystems, and it plays an important role in regulating climate change, the carbon cycle, and energy exchange. And permafrost is extremely sensitive to climate change. In particular, aboveground vegetation on permafrost has great sensitivity to that change. The permafrost zone of northeastern China, within middle and high latitudes of the northern hemisphere, is the second-largest region of permafrost in China. It is at the southern edge of the Eurasian cryolithozone. This study analyzes growing-season spatiotemporal variation of the normalization difference vegetation index (NDVI) in this permafrost zone and the correlation between NDVI and climate variables during 1981-2014. Mean growing-season NDVI significantly increased by 0.0028 yr⁻¹ over the entire permafrost zone. The spatial dynamics of vegetation cover in the zone had strong heterogeneity on the pixel scale. Pixels that showed increasing trends accounted for 80% of the permafrost area, and were mostly found in the permafrost zone with the exception of western steppe regions. Pixels that showed decreasing trends (approximately 20% of the permafrost area) were mainly in the cultivated and steppe portions of the study area. Our results indicated that temperature was the dominant influence on vegetation growth during the growing season in most permafrost zones.

Characterization of air pollution index and its affecting factors in industrial urban areas in northeastern China

75%

Gong J. , Hu Y. , Liu M. , Bu R. , Chang Y. , Li C. , Wu W.

Polish Journal of Environmental Studies

2015

tom 24

nr 4

The air pollution index (API) and meteorological parameters in four cities (Harbin, Changchun, Shenyang, and Dalian) in north-eastern China were analyzed in 2001-12, to study the characterization of the API and its influential factors. According to the monitoring data, air pollution is a significant problem in northeastern China, with all four industrial cities heavily polluted, especially Shenyang. During the study period, the API in the cities was down slightly. Clear interannual, seasonal, and monthly variations of air pollution were determined, which indicated that air quality was poorest in winter (especially November and December), but improved in summer (especially July and August). Air quality level varied in different weather conditions. Water vapor pressure was the most influential meteorological factor with regard to the API, followed by air temperature and surface pressure. Wind direction was found to be an important influential factor with regard to air pollution, because air flow from different directions has an impact on the accumulating or cleaning process of pollutants. However, the dominant meteorological factors influencing air pollution varied in each of the cities in terms of season, time scale, and level of air pollution. Our results highlight the significant impact of synoptic weather on API in northeastern China.

Land use regression modelsusing satellite aerosol optical depth observations and 3D building data from the central cities of Liaoning Province, China

63%

Gong J. , Hu Y. , Liu M. , Bu R. , Chang Y. , Bilal M. , Li C. , Wu W. , Ren B.

2016

tom 25

nr 3