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access icon free Sampled-data control of fuzzy systems based on the intelligent digital redesign method via an improved fuzzy Lyapunov functional approach

© The Institution of Engineering and Technology
Received 06/04/2017, Accepted 26/09/2017, Revised 21/08/2017, Published 27/09/2017

This study presents a linear matrix inequality (LMI) approach to the sampled-data control of Takagi–Sugeno fuzzy systems, based on the intelligent digital redesign (IDR) technique. The objective of the IDR is to design a digital control system whose trajectory closely matches that of a given well-constructed analogue control system by minimising the state-matching error. In this study, state-matching performance is enhanced by using a continuous-time state-matching criterion, which guarantees that the state-matching error is minimised through the entire time interval. Unlike previous studies, mismatched information of membership functions for both analogue and digital control systems is directly manipulated. Moreover, the authors introduce an improved fuzzy Lyapunov functional that consists of both membership functions for analogue and digital control systems, which relaxes the conservativeness of LMI conditions. Finally, two examples demonstrating the effectiveness of the authors' method are provided.

Inspec keywords: digital control; minimisation; linear matrix inequalities; fuzzy control; Lyapunov methods; sampled data systems; control system synthesis; continuous time systems; fuzzy systems

Other keywords: state-matching performance; membership functions; analogue control system; LMI approach; continuous-time state-matching criterion; digital control system; intelligent digital redesign method; state-matching error minimization; linear matrix inequality; improved fuzzy Lyapunov functional approach; Takagi-Sugeno fuzzy systems; IDR technique; sampled-data control

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

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