2012 American Control Conference (ACC) 2012
DOI: 10.1109/acc.2012.6314733
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Undamped nonlinear consensus using integral Lyapunov functions

Abstract: Abstract-This paper analyzes a class of nonlinear consensus algorithms where the input of an agent can be decoupled into a product of a gain function of the agents own state, and a sum of interaction functions of the relative states of its neighbors. We prove the stability of the protocol for both single and double integrator dynamics using novel Lyapunov functions, and provide explicit formulas for the consensus points. The results are demonstrated through simulations of a realistic example within the framewo… Show more

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Cited by 15 publications
(14 citation statements)
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References 25 publications
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“…Following a similar analysis as in the proof of Theorem 1 of [36], we can show that, under the condition that Assumption 1 holds at each time t , S y1 S S y2 ¤ ; for the case of V 1 .y.t // > 0 at each time t . We next consider three different cases to analyze the time derivative of V 1 .…”
Section: Lemmamentioning
confidence: 83%
See 2 more Smart Citations
“…Following a similar analysis as in the proof of Theorem 1 of [36], we can show that, under the condition that Assumption 1 holds at each time t , S y1 S S y2 ¤ ; for the case of V 1 .y.t // > 0 at each time t . We next consider three different cases to analyze the time derivative of V 1 .…”
Section: Lemmamentioning
confidence: 83%
“…Under the condition that Assumption holds at each time t , it is trivial to show that V1(y)0 and V 1 ( y ) = 0 if and only if y 1 = y 2 = ⋯ = y n = 0 from the facts that msubnormalmaxiMathClass-rel=0MathClass-punc,1MathClass-punc,MathClass-rel⋯MathClass-punc,n{yi}0 and min i = 0,1, ⋯ , n { y i } ⩽ 0. Motivated by , we construct the following sets Sy1MathClass-rel={}iMathClass-bin+MathClass-punc:yiMathClass-bin+MathClass-rel=msubnormalmaxiMathClass-rel=0MathClass-punc,1MathClass-punc,MathClass-rel⋯MathClass-punc,n{yi}MathClass-punc,msubnormalminkMathClass-rel∈falsemml-overlineN¯iMathClass-bin+ykMathClass-rel<yiMathClass-bin+, Sy2MathClass-rel={}iMathClass-bin−MathClass-punc:yiMathClass-bin−MathClass-rel=msubnormalminiMathClass-rel=0MathClass-punc,1MathClass-punc,MathClass-rel⋯MathClass-punc,n{yi}MathClass-punc,msubnormalmaxkMathClass-rel∈falsemml-overlineN¯iMathClass-bin−ykMathClass-rel>yiMathClass-bin−. Following a similar analysis as in the proof of Theorem of , we can show that, under the condition that Assumption holds at each time t , Sy1MathClass-op...…”
Section: Coordinated Tracking Over a Directed Switching Communicationmentioning
confidence: 99%
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“…Following a similar analysis as in the proof of theorem 1 of Andreasson et al, 37 it is trivial to show that, under the condition that Assumption 2 holds, S 1 ∪ S 2 ≠ ∅ for the case of W 1 ( hu ) > 0. S 1 ∪ S 2 ≠ ∅ can be divided into three different cases: S 1 ≠ ∅, S 2 = ∅ and S 1 = ∅, S 2 ≠ ∅ and S 1 ≠ ∅, S 2 ≠ ∅.…”
Section: Finite-time Formation Controller Designmentioning
confidence: 89%
“…Motivated by Meng et al, we construct the following sets: S1=false{i+:εhui+=maxi=0,1,,nfalse{εhuifalse},minkÑi+εhuk<εhui+false}, S2=false{i:εhui=mini=0,1,,nfalse{εhuifalse},maxkÑiεhuk>εhuifalse}. Following a similar analysis as in the proof of theorem 1 of Andreasson et al, it is trivial to show that, under the condition that Assumption 2 holds, S 1 ∪ S 2 ≠∅ for the case of W 1 ( ε hu )>0. S 1 ∪ S 2 ≠∅ can be divided into three different cases: S 1 ≠∅, S 2 =∅ and S 1 =∅, S 2 ≠∅ and S 1 ≠∅, S 2 ≠∅.…”
Section: Finite‐time Formation Controller Designmentioning
confidence: 99%