Positivity and Stability of Continuous-Time Stochastic Linear Systems
This paper is concerned with the positivity and stability of linear systems in continuous-time form with stochastic disturbances. Firstly, the definition of stochastic positivity in the sense of probability is introduced, which characterizes the minimum level for a stochastic linear system to be positive. Secondly, through rigorous analysis, sufficient criterion is derived under which the stochastic differential equation is stochastically positive in the sense of probability. Next, by resorting to the properties of Metzler matrices, mathematical expectation of the solution for the stochastic linear system is investigated to be always positive under some mild restrictions. Then, the exponentially p-moment stability is addressed for the stochastic linear positive system. Finally, two numerical examples are provided to demonstrate the applicability and effectiveness of the derived theoretical results.
KeywordsStochastic linear systems Metzler matrix Positivity Stability
This work was supported in part by the National Natural Science Foundation of China under Grant 61673110 and Grant 61833005, and in part by the Jiangsu Provincial Key Laboratory of Networked Collective Intelligence under Grant BM2017002.
- 2.Bolzern P., Colaneri P., Nicolao G.De.: Stabilization via switching of positive Markov jump linear systems. In: 53rd IEEE Conference on Decision and Control, pp. 2359–2364, (2014)Google Scholar
- 8.Jacquez, J.A.: Compartmental Analysis in Biology and Medicine, pp. 1–3. The University of Michigan Press, USA (1985)Google Scholar
- 12.Kang, Z., Wang, Q., Huang, L., Liu, Z.: Parameter optimization of active-disturbance-rejection controller based on improved genetic algorithm. Inf. Control. 37(5), 588–592(598) (2008)Google Scholar
- 14.Mao, X.: Stochastic Differential Equations and Applications, pp. 48–127. Horwood Publishing, Chichester (1997)Google Scholar