ij ij ij
(4)
ij vij
and uij
as 1。 As seen from Fig。 2, the reverse
that the system approached to the sliding surface would
transmission error of the output layer is described as
also be correspondingly reduced and the time to reach
M M
( f (4) (I (4) ))
the sliding surface would be longer。 In order to meet the
(4) j j
j (I (4) )
( f (4) (I (4) ))
(I (4) )
rapid nature of the system and reduce the chattering, the
j j j j
particle swarm optimization algorithm is adopted to
(4) (4)
d j Oj
As w(3) 1,
(15)
the rule-layer had only the reverse
optimize the values of cx, cl, cθ, α, ε1, k1, ε2 and k2。
Similar to other evolutionary algorithms, PSO
algorithm works well with the fitness value of each
transmission error。
(3) M
M
( f (3) (I (3) ))
particle based on the notations of “group” and “evolution” [16]。 In the original PSO, the position of
j
(I (3) ) ( f (3) (I (3) ))
(I (3) )
j j j j
each particle in the swarm represents a possible solution。
(4) (4)
k jk
k
(16)
The position and velocity of particle i at iteration n are denoted as xi, d(n) and vi, d(n), respectively。 The new
The degree of membership layer anti-pass error is velocity at the next iteration, vi,d(n+1), is calculated by
M M
( f (2) (I (2) ))
using its current velocity vi,d(n), the distance between the
(2) j j
j
(I (2) )
( f (2) (I (2) ))
(I (2) )
particle’s best previous position pi,d(n) and xi,d(n), as well 桥式起重机智能防摆控制英文文献和中文翻译(7):http://www.youerw.com/fanyi/lunwen_97253.html