Abstract
A design method is established for the mixed H 2 / H ∞ output-feedback control of stochastic nonlinear systems with multiplicative noise. Firstly, using T-S fuzzy rules, we obtain a fuzzy model to approximate the original nonlinear system. Then, by Schur’s complement, the suboptimal H 2 / H ∞ output-feedback control design is transformed into a two-step convex optimization problem. A numerical example is given to show the effectiveness of the proposed method.
Highlights
One of the objectives of system control is to design a controller for the object model so that the closed-loop system achieves good performance while ensuring internal stability [1,2,3,4]
Linearizing the nonlinear system has become mature technology to treat the nonlinear problems. [26] introduced a suitable linear model gained by the T-S fuzzy rule to approximate a nonlinear system. [27] designed a mixed H2/H∞ controller for nonlinear systems based on fuzzy observer
Compared with [27], in which the considered system model does not contain multiplicative noise, it is clear that H2/H∞ control for nonlinear systems with multiplicative noise has broader application prospects. e other contribution of this paper is that the suboptimal H2/H∞ output-feedback control design is transformed into a two-step convex optimization problem, which is convenient for solving by MATLAB efficiently
Summary
One of the objectives of system control is to design a controller for the object model so that the closed-loop system achieves good performance while ensuring internal stability [1,2,3,4]. [26] introduced a suitable linear model gained by the T-S fuzzy rule to approximate a nonlinear system. [27] designed a mixed H2/H∞ controller for nonlinear systems based on fuzzy observer. Robust control for stochastic nonlinear systems is definitely worthy both from the theoretical and practical application views. E other contribution of this paper is that the suboptimal H2/H∞ output-feedback control design is transformed into a two-step convex optimization problem, which is convenient for solving by MATLAB efficiently. We adopt the following notations: tr(A): the trace of matrix A AT: the transpose of matrix A A ≥ 0(A > 0): a positive semidefinite (positive definite) matrix A I: the identity matrix ‖x‖: the Euclidean 2-norm of the n-dimensional real vector x
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
