For switched linear system with colored measurement noises,the identification difficulties of this system are that there exist unknown switching information,unknown middle variables and noise terms in the information ...For switched linear system with colored measurement noises,the identification difficulties of this system are that there exist unknown switching information,unknown middle variables and noise terms in the information vector.For the mentioned issues,the fuzzy clustering and the multi-innovation recursive identification algorithm are used to deal with these problems.Firstly,the mode detection is transformed into the detection of membership degree values confirmed by the fuzzy clustering method,and the problem of mode detection is solved by judgment and decision of the fuzzy membership values.Moreover,the multi-innovation recursive identification algorithm based on the generalized auxiliary model is proposed to estimate the parameters of the switched linear system with colored noises.Finally,the effectiveness of the proposed method is verified by the results of the simulation example.展开更多
The studying motivation of this paper is that there exist many modeling issues of nonuniformly sampling nonlinear systems in industrial systems.Based on multi-model modeling principle,the corresponding model of non-un...The studying motivation of this paper is that there exist many modeling issues of nonuniformly sampling nonlinear systems in industrial systems.Based on multi-model modeling principle,the corresponding model of non-uniformly sampling nonlinear systems is described by the nonlinear weighted combination of some linear models at local working points.Fuzzy modeling based on multimodel scheme is a common method to describe the dynamic process of non-linear systems.In this paper,the fuzzy modeling method of non-uniformly sampling nonlinear systems is studied.The premise structure of the fuzzy model is confirmed by GK fuzzy clustering,and the conclusion parameters of the fuzzy model are estimated by the recursive least squared algorithm.The convergence perfromance of the proposed identification algorithm is given by using lemmas and martingale theorem.Finally,the simulation example is given to demonstrate the effectiveness of the proposed method.展开更多
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...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.展开更多
基金supported by the National Natural Science Foundation of China(61863034)
文摘For switched linear system with colored measurement noises,the identification difficulties of this system are that there exist unknown switching information,unknown middle variables and noise terms in the information vector.For the mentioned issues,the fuzzy clustering and the multi-innovation recursive identification algorithm are used to deal with these problems.Firstly,the mode detection is transformed into the detection of membership degree values confirmed by the fuzzy clustering method,and the problem of mode detection is solved by judgment and decision of the fuzzy membership values.Moreover,the multi-innovation recursive identification algorithm based on the generalized auxiliary model is proposed to estimate the parameters of the switched linear system with colored noises.Finally,the effectiveness of the proposed method is verified by the results of the simulation example.
基金the National Natural Science Foundation of China under Grant Nos.61863034and 51667021。
文摘The studying motivation of this paper is that there exist many modeling issues of nonuniformly sampling nonlinear systems in industrial systems.Based on multi-model modeling principle,the corresponding model of non-uniformly sampling nonlinear systems is described by the nonlinear weighted combination of some linear models at local working points.Fuzzy modeling based on multimodel scheme is a common method to describe the dynamic process of non-linear systems.In this paper,the fuzzy modeling method of non-uniformly sampling nonlinear systems is studied.The premise structure of the fuzzy model is confirmed by GK fuzzy clustering,and the conclusion parameters of the fuzzy model are estimated by the recursive least squared algorithm.The convergence perfromance of the proposed identification algorithm is given by using lemmas and martingale theorem.Finally,the simulation example is given to demonstrate the effectiveness of the proposed method.
基金Program for New Century Excellent Talents in University of China (NCET-05-0607)National Natural Science Fou-ndation of China (No.60774010)Project for Fundamental Research of Natural Sciences in Universities of Jingsu Province (No.07KJB510114)
文摘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.
