A more general class of stochastic nonlinear systems with Markovian switching are considered in this paper.As ...
Wu Zhaojing1,Xie Xuejun2 1.School of Mathematics and Information Science,Yantai University,Yantai 264005,P.R.China 188.com 2.Institute of Automation,Qufu Normal University,Qufu 273165,P.R.China
＜正＞This paper investigates the output-feedback stabilization problem for a class of high-order stochastic nonl...
LI Wuquan~1,LIU Xiaohua~1,ZHANG Siying~2 1.School of Mathematics and Information,Ludong University,Yantai 264025,P.R.China 2.College of Information Science and Engineering,Northeastern University,Shenyang 110819,P.R.China
＜正＞This paper considers a concrete stochastic nonlinear systems with stochastic unmeasurable inverse dynamic.M...
Na Duan~1,Xin Yu~2,Xue-Jun Xie~1 1.School of Electrical Engineering & Automation,Xuzhou Normal University,Xuzhou,Jiangsu Province,221116,China 2.School of Automation,Southeast University,Nanjing,Jiangsu Province,210096,China
For a class of discrete-time systems with unmodeled dynamics and bounded disturbance, the design and analysis of robust indirect model reference adaptive control （MRAC） with normalized adaptive law are investigated. The main work includes three parts. Firstly, it is shown that the constructed parameter estimation algorithm not only possesses the same properties as those of traditional estimation algorithms, but also avoids the possibility of division by zero. Secondly, by establishing a relationship between the plant parameter estimate and the controller parameter estimate, some similar properties of the latter are also established. Thirdly, by using the relationship between the normalizing signal and all the signals of the closed-loop system, and some important mathematical tools on discrete-time systems, as in the continuous-time case, a systematic stability and robustness analysis approach to the discrete indirect robust MRAC scheme is developed rigorously.
This paper considers a class of stochastic nonlinear systems with linearly bounded unmeasurable states from th...
Duan Na1,Xie Xuejun1,2 1.School of Electrical Engineering&Automation,Xuzhou Normal University,Xuzhou 221116,P.R.China 2.Institute of Automation,Qufu Normal University,Qufu Shandong 273165,P.R.China
In this paper, for a class of high-order stochastic nonlinear systems with zero dynamics which are neither necessarily feedback linearizable nor affine in the control input, the problem of state feedback stabilization is investigated for the first time. Under some weaker assumptions, a smooth state feedback controller is designed, which ensures that the closed-loop system has an almost surely unique solution on [0,∞）, the equilibrium at the origin of the closed-loop system is globally asymptotically stable in probability, and all the states can be regulated to the origin almost surely. A simulation example demonstrates the control scheme.
This paper considers a concrete stochastic nonlinear system with stochastic unmeasurable inverse dynamics. Motivated by the concept of integral input-to-state stability （iISS） in deterministic systems and stochastic input-to-state stability （SISS） in stochastic systems, a concept of stochastic integral input-to-state stability （SiISS） using Lyapunov functions is first introduced. A constructive strategy is proposed to design a dynamic output feedback control law, which drives the state to the origin almost surely while keeping all other closed-loop signals almost surely bounded. At last, a simulation is given to verify the effectiveness of the control law.
