Decentralised Fully Probabilistic Design for Stochastic Networks with
Multiplicative Noise
Abstract
In this paper, a novel decentralised control framework based on
decentralised fully probabilistic design (DFPD) is proposed for a class
of stochastic dynamic complex systems with multiple multiplicative
noises. Compared with the existing conventional DFPD, the new procedure
is improved by modifying the Riccati equation in order to deal with
multiple multiplicative noises. Considering the stochastic nature of
complex systems, the systems’ dynamical behaviours are fully
charaterised by probabilistic state-space models. In this way, a
complete description of the components of the subsystems is provided. In
addition, probabilistic message passing architecture is introduced to
provide communication between neighbouring subsystems and to harmonise
the actions between the local nodes. To illuminate the effectiveness of
the proposed framework, a three inverted pendulum system numerical
example is presented and the results are compared with the conventional
DFPD.