Exponential Stabilisation of Continuous-time Periodic Stochastic Systems by Feedback Control Based on Periodic Discrete-time Observations

Since Mao in 2013 discretised the system observations for stabilisation problem of hybrid SDEs (stochastic differential equations with Markovian switching) by feedback control, the study of this topic using a constant observation frequency has been further developed. However, time-varying observation frequencies have not been considered. Particularly, an observational more efficient way is to consider the time-varying property of the system and observe a periodic SDE system at the periodic time-varying frequencies. This study investigates how to stabilise a periodic hybrid SDE by a periodic feedback control, based on periodic discrete-time observations. This study provides sufficient conditions under which the controlled system can achieve pth moment exponential stability for p > 1 and almost sure exponential stability. Lyapunov's method and inequalities are main tools for derivation and analysis. The existence of observation interval sequences is verified and one way of its calculation is provided. Finally, an example is given for illustration. Their new techniques not only reduce observational cost by reducing observation frequency dramatically but also offer flexibility on system observation settings. This study allows readers to set observation frequencies according to their needs to some extent

Probabilistic control for uncertain systems

In this paper a new framework has been applied to the design of controllers which encompasses nonlinearity, hysteresis and arbitrary density functions of forward models and inverse controllers. Using mixture density networks, the probabilistic models of both the forward and inverse dynamics are estimated such that they are dependent on the state and the control input. The optimal control strategy is then derived which minimizes uncertainty of the closed loop system. In the absence of reliable plant models, the proposed control algorithm incorporates uncertainties in model parameters, observations, and latent processes. The local stability of the closed loop system has been established. The efficacy of the control algorithm is demonstrated on two nonlinear stochastic control examples with additive and multiplicative noise

Global robust output regulation for a class of affine singular nonlinear systems

The global robust output regulation problem of the singular nonlinear system is investigated. Motivated by the input-output linearization of the normal affine nonlinear system, a global diffeomorphism map is designed under the assumption that the singular nonlinear system has a strong relative degree. The global diffeomorphism map transfers the singular nonlinear system into a new singular nonlinear system with a special structure. Attaching an internal model to the new singular nonlinear system yields an augmented singular nonlinear system and the global robust stabi-lization solution of the augmented system implies the global robust output regulation solution of the original singular nonlinear system. Then the global stabilization problem is solved by some appropri-ate assumptions and the solvability conditions of the global robust output regulation problem are established. Finally, a simulation example is given to illustrate the design approach.The global robust output regulation problem of the singular nonlinear system is investigated. Motivated by the input-output linearization of the normal affine nonlinear system, a global diffeomorphism map is designed under the assumption that the singular nonlinear system has a strong relative degree. The global diffeomorphism map transfers the singular nonlinear system into a new singular nonlinear system with a special structure. Attaching an internal model to the new singular nonlinear system yields an augmented singular nonlinear system and the global robust stabilization solution of the augmented system implies the global robust output regulation solution of the original singular nonlinear system. Then the global stabilization problem is solved by some appropriate assumptions and the solvability conditions of the global robust output regulation problem are established. Finally, a simulation example is given to illustrate the design approach.National Natural Science Foundation of China [61374035]; Fundamental; Research Funds for the Central Universities [20720150177