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access icon free Intelligent digital redesign for T–S fuzzy systems: sampled-data filter approach

© The Institution of Engineering and Technology
Received 01/09/2017, Accepted 23/02/2018, Revised 13/12/2017, Published 27/02/2018

This study proposes an intelligent digital redesign (IDR) technique for sampled-data fuzzy filters of non-linear systems. The technique constructs a closed-loop system with predesigned continuous-time and sampled-data filters based on the Takagi–Sugeno (T–S) fuzzy model. The closed-loop systems ensure asymptotic stability and state-matching condition in the IDR problem. Unlike previous techniques, the proposed method solves the IDR problem without a discretization process which degrades the IDR performance. Sufficient conditions for solving the IDR problem are proposed and derived in terms of linear matrix inequalities. In addition, the performance recovery of the sampled-data fuzzy filter is shown. Finally, the feasibility of the proposed technique is demonstrated in two simulation examples.

Inspec keywords: asymptotic stability; nonlinear control systems; linear matrix inequalities; closed loop systems; sampled data systems; filtering theory; fuzzy control; fuzzy systems; control system synthesis; continuous time systems

Other keywords: sampled-data filter approach; IDR performance; Takagi-Sugeno fuzzy model; linear matrix inequalities; state-matching condition; asymptotic stability; closed-loop system; predesigned continuous-time; nonlinear systems; intelligent digital redesign technique; IDR problem; sampled-data filters; T–S fuzzy systems; sampled-data fuzzy filter

Subjects: Control system analysis and synthesis methods; Stability in control theory; Nonlinear control systems; Fuzzy control; Discrete control systems; Algebra

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