The Bridge - Issue 2, 2018 - 22

Feature
constraint estimation error are two important factors
to evaluate the critic NN approximation performance.
To better learn the ideal stochastic optimal cost
function, the critic NN can be tuned by using two
estimation errors (i.e.
) as

The flowchart of proposed design is shown
in Figure 3.

(13)

C. Actor NNs Estimation of Stochastic Optimal
Flocking Control and Worst Case Disturbances
The two actor NNs for optimal control and worst
case disturbances can be estimated as
(14)
where
are the approximated
weights for control and disturbance actor NNs,
respectively. Specifically, the estimation errors can be
derived as

(15)
Figure 3. Flowchart of the proposed finite horizon
optimal design

To better tune two actor NNs, the novel update laws
are proposed by using the estimation errors defined
in (34) as

(16)
with two actor NNs tuning parameters α u, α d
satisfying and 0<α u<1 and 0<α d<1. Overall,

THE BRIDGE



Table of Contents for the Digital Edition of The Bridge - Issue 2, 2018

Contents
The Bridge - Issue 2, 2018 - Cover1
The Bridge - Issue 2, 2018 - Cover2
The Bridge - Issue 2, 2018 - Contents
The Bridge - Issue 2, 2018 - 4
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