Adaptive event-triggered output feedback control for uncertain networked T–S fuzzy system with data loss and bounded disturbance: An efficient MPC strategy

This paper proposes an adaptive event-triggered (AET) control, efficient model predictive control (EMPC) and output feedback control co-design approach for uncertain nonlinear systems over networks with bounded disturbance and data loss. The AET control involving a novel adaptive law is utilized to further reduce data transmission in networked control systems. Involving the technique of quadratic boundedness (QB), a class of output feedback predictive controllers based on the EMPC strategy are designed by minimizing several offline optimization problems and one online optimization problem. The approach in this paper, which transfers abundant online design work to offline, provides an offline determined augmented control invariant set for significantly reducing real-time computational load. Through the introduction of a novel matrix partition method moreover, the conventional online optimization problem of EMPC is transformed into a new form which is convenient to solve in this paper. A numerical example including some comparative experiments is proposed to clarify the availability of this approach.