Cooperative guidance and control for rendezvous with uncooperative target based on Augment Proportional Navigation

Author(s):  
Weilin Wang ◽  
Lei Chen ◽  
Yongjun Lei ◽  
Yangang Liang
2016 ◽  
Vol 49 (19) ◽  
pp. 165-170 ◽  
Author(s):  
E. Altendorf ◽  
M. Baltzer ◽  
Y. Canpolat ◽  
D. Lopez ◽  
C. Schreck ◽  
...  

Ergonomics ◽  
2014 ◽  
Vol 57 (3) ◽  
pp. 343-360 ◽  
Author(s):  
Frank Ole Flemisch ◽  
Klaus Bengler ◽  
Heiner Bubb ◽  
Hermann Winner ◽  
Ralph Bruder

Author(s):  
Ke-Bo Li ◽  
Wen-Shan Su ◽  
Lei Chen

The interception of high-speed target with an arbitrary maneuvering acceleration causes serious troubles to the guidance and control system design of airborne missile. A novel guidance law based on the classical differential geometry curve theory was proposed not long ago. Although it is believed and numerically demonstrated that this differential geometric guidance law (DGGL) is superior to the classical pure proportional navigation (PPN) in intercepting high-speed targets, its performance has not been thoroughly analyzed. In this paper, using the Lyapunov-like approach, the performance of DGGL against the high-speed target with an arbitrary but upper-bounded maneuvering acceleration is well studied. The upper bounds of the LOS rate and commanded acceleration of DGGL are obtained, and conditions that guarantee the capture of this type of maneuvering target are also presented. The nonlinear relative dynamics between the missile and target is taken into full account. Finally, the proposed theoretical findings are demonstrated by numerical simulation examples.


1998 ◽  
Vol 120 (3) ◽  
pp. 353-359 ◽  
Author(s):  
J. L. Dohner

Cooperative micro-robotic scent tracking vehicles are designed to collectively “sniff out” locations of high scent concentrations in unknown, geometrically complex environments. These vehicles are programed with guidance and control algorithms that allow inter cooperation among vehicles. In this paper, a cooperative guidance and control algorithm for scent tracking micro-robotic vehicles is presented. This algorithm is comprised of a sensory compensation sub-algorithm using point source cancellation, a guidance sub-algorithm using gradient descent tracking, and a control sub-algorithm using proportional feedback. The concepts of social rank and point source cancellation are new concepts introduced within. Simulation results for cooperative vehicles swarms are given. Limitations are discussed.


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