Uncertainty characterization for robust MPC using an approximate convex hull method

Author(s):  
Hossein Sartipizadeh ◽  
Tyrone L. Vincent
2017 ◽  
Vol 431 ◽  
pp. 34-47 ◽  
Author(s):  
Amieibibama Joseph ◽  
Christine M. Sands ◽  
Peter D. Hicks ◽  
Howard W. Chandler

2014 ◽  
Vol 571-572 ◽  
pp. 721-724
Author(s):  
Xiu Xun Huang ◽  
Ji Ting Zhou ◽  
Chen Ling ◽  
Wen Jun Zhang

A novel three-dimensional (3D) convex hull method is proposed, which is called dimensionality reduction convex hull method (DRCH).Through having 3d point set map to 2d plane, most initial 3D points in the convex hull are removed. Then, the remaining points are to generate 3D convex hull using any convex hull algorithm. The experiment demonstrates 3D DRCH is faster than general 3D convex hull algorithms. Its time complexity is O(r log r), where r is the number of points not in the hull. And DRCH can be generalized to higher-dimensional problems.


2019 ◽  
Vol 67 (1) ◽  
pp. 27 ◽  
Author(s):  
Sophie L. Cross ◽  
Sean Tomlinson ◽  
Michael D. Craig ◽  
Philip W. Bateman

Understanding the behavioural responses of animals to habitat change is vital to their conservation in landscapes undergoing restoration. Studies of animal responses to habitat restoration typically assess species presence/absence; however, such studies may be restricted in their ability to show whether restoration is facilitating the return of self-sustaining and functional fauna populations. We present a case study using VHF/GPS tracking of a young adult perentie (Varanus giganteus), to demonstrate the range of applications of the Time Local Convex Hull method of home-range construction in analysing the behavioural responses of fauna to habitat change and restoration. Presence/absence studies provide single point locations of an animal, and the Minimum Convex Polygon method provides an invariant estimate of habitat use across the whole home range. However, the Time Local Convex Hull method provides a useful method for assessing movement and behavioural responses of fauna to habitat change and restoration, and the specific habitat requirements for the long-term support of populations. The breadth and multidimensionality of data generated indicates strongly that understanding the complex interactions between animals and their environment is fundamental to their conservation in the face of ever-increasing rates of human-induced habitat change and degradation.


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