Output Feedback Predictive Control of Interval Type-2 T–S Fuzzy Systems With Markovian Packet Loss

This paper investigates the synthesis approach of output feedback model predictive control (OFMPC) for nonlinear systems over networks where the data quantization and packet loss may occur simultaneously. The nonlinear system, which is subjected to parameter uncertainties, is represented by the interval type-2 Takagi-Sugeno fuzzy model. The quantization error is treated as sector bound uncertainties by using the sector bound approach, and a binary Markov chain is introduced to characterize the phenomenon of packet loss of the networked control systems (NCSs). The synthesis approach of OFMPC provided in this paper involves an offline designed state observer using the linear matrix inequality technique and an online model predictive control optimization problem, which minimizes an upper bound of the expect value of the infinite horizon performance cost based on the obtained estimated state. A new technique of refreshing the estimation error bound, which plays the key role of guaranteeing the recursive feasibility of optimization problem, is provided. An example is given to demonstrate the effectiveness of the proposed new design techniques.