Review of the Latest Progress in Controllability of Stochastic Linear Systems and Stochastic GE-Evolution Operator

According to the spatial dimension, equation type, and time sequence, the latest progress in controllability of stochastic linear systems and some unsolved problems are introduced. Firstly, the exact controllability of stochastic linear systems in finite dimensional spaces is discussed. Secondly, the exact, exact null, approximate, approximate null, and partial approximate controllability of stochastic linear systems in infinite dimensional spaces are considered. Thirdly, the exact, exact null and impulse controllability of stochastic singular linear systems in finite dimensional spaces are investigated. Fourthly, the exact and approximate controllability of stochastic singular linear systems in infinite dimensional spaces are studied. At last, the controllability and observability for a type of time-varying stochastic singular linear systems are studied by using stochastic GE-evolution operator in the sense of mild solution in Banach spaces, some necessary and sufficient conditions are obtained, the dual principle is proved to be true, an example is given to illustrate the validity of the theoretical results obtained in this part, and a problem to be solved is introduced. The main purpose of this paper is to facilitate readers to fully understand the latest research results concerning the controllability of stochastic linear systems and the problems that need to be further studied, and attract more scholars to engage in this research.

Optimal control of large-scale singular linear systems via hierarchical strategy

This paper states a hierarchical strategy of large-scale singular linear system in which the system is composed of J singular linear subsystems with interconnections. Among hierarchical strategies, the two-level optimization conditions based on Interaction Prediction Method (IPM) are derived such that whole large-scale singular system is optimized. Based on the two-level coordination method, the optimization analysis and controller design of large-scale singular linear system is discussed. For this purpose, two decentralized nonlinear state feedback controllers are designed for each subsystem, such that the whole closed-loop linear system is optimized. These conditions are used to extract two IPM algorithms. Then, by using both algorithms, two numerical examples are given to confirm the analytical results and illustrate the effectiveness of the proposed method.