Zonotopic interval estimation for nonlinear systems with event-triggered protocols

This paper investigates the zonotope-based interval estimation problem for event-triggered nonlinear systems with incrementally quadratic constraint and unknown-but-bounded uncertainties from process disturbance and measurement noise. Considering the restricted communication bandwidth, an event-triggered communication protocol is deployed in the sensor-to-observer channel, based on which an event-triggered observer is constructed for nonlinear systems having incremental quadratic constraints. A co-design method of nonlinear observer and event-triggered protocol is obtained to ensure the stability and ℓ∞ index of the estimation error dynamic. Based on the designed event-triggered observer, a zonotope-based interval estimation algorithm is designed for the purpose of giving the intervals enclosing admissible values of system state. The mean value extension coalesce into natural interval extension is utilized to deal with the nonlinear transformation of system, and the enclosing zonotope of ellipsoid is introduced to tackle the extra uncertainties induced by event-triggered protocol. Lastly, the results of a simulation on a hyper-chaotic Chen system are provided to confirm the validity of the presented methodology.