In this study, a novel intelligent digital redesign (IDR) technique is proposed for the sampled-data fuzzy controller of the non-linear system with packet losses. For the IDR development, the non-linear system is represented in the Takagi–Sugeno fuzzy model and the packet loss is assumed to be an independent, identically distributed Bernoulli random process. After introducing the traditional IDR technique, the closed-loop system with state-matching error and the state-matching error cost function are achieved for the development of the novel IDR technique. In the discrete-time Lyapunov sense, the exponential mean-square stability is guaranteed while minimising the state-matching error, and its sufficient condition is derived into linear matrix inequalities. Two examples are provided to verify the effectiveness of the proposed technique by comparison.

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.