A new control method that considers all sources of uncertainty and noises that might affect the time evolutions of quantum physical systems is introduced. Under the proposed approach, the dynamics of quantum systems are characterised by probability density functions (pdfs), thus providing a complete description of their time evolution. Using this probabilistic description, the proposed method suggests the minimisation of the distance between the actual pdf that describes the joint distribution of the time evolution of the quantum system and the external electric field, and the desired pdf that describes the system target outcome. We start by providing the control solution for quantum systems that are characterised by arbitrary pdfs. The obtained solution is then applied to quantum physical  systems characterised by Gaussian pdfs and the form of the optimised controller is elaborated. Finally, the proposed approach is demonstrated on a real molecular system and two spin systems showing the effectiveness and simplicity of the method.

In this paper, we propose a unified probabilistic decentralised control and message passing framework for real time control of the electrical grid which enables the development of the future smart grid. The key elements of the proposed framework are the design of local randomised controllers and probabilistic message passing methodology which enables the coordination between the designed local controllers to account for optimisation considerations on the system operation. Within the proposed framework, the electric grid is decomposed into a number of control areas. Additionally, since the frequency is the ubiquitous grid state variable, representing the balancing of active power generation and consumption, the proposed framework is demonstrated based on local Load Frequency Control (LFC). Simulation studies involving a six-area power system and three interconnection schemes are carried out to illustrate the applicability and effectiveness of the proposed approach.

This paper proposes a novel probabilistic framework for the design of probabilistic message passing mechanism for complex and large dynamical systems that are operating and governing under a decentralized way. The proposed framework considers the evaluation of probabilistic messages that can be passed between mutually interacting quasi-independent subsystems that will not be restricted by the assumption of homogeneity or conformability of the subsystems components. The proposed message passing scheme is based on the evaluation of the marginal density functions of the states that need to be passed from one subsystem to another. An additional contribution is the development of stochastic controllability analysis of the controlled subsystems that constitute a complex system. To facilitate the understanding and the analytical analysis of the proposed message passing mechanism and the controllability analysis, theoretical developments are demonstrated on linear stochastic Gaussian systems.

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.