Observer-Based Output Feedback MPC for T–S Fuzzy System With Data Loss and Bounded Disturbance

This paper investigates the output feedback model predictive control (OFMPC) for Takagi–Sugeno fuzzy networked control systems with bounded disturbance, where data quantization and data loss occur simultaneously. The quantization error is treated as sector bound uncertainties by using the sector bound approach and the data loss process is modeled as a time-homogeneous Markov chain. Invoking ${S}$ -procedure and the notion of quadratic boundedness which can specify closed-loop stability for system with disturbance, the state observer is offline designed and the networked output feedback model predictive controller is provided which explicitly considers the satisfaction of input constraints. Two online synthesis algorithms of OFMPC are presented, one parameterizing the infinite horizon control moves into a single feedback law, the other into one free control move followed by the single feedback law based on the state observer. A new formula is introduced to refresh the ellipsoidal bound of estimation error which can guarantee the recursive feasibility of optimization problem. An example is given to demonstrate the effectiveness of the proposed new design techniques.