Sensor fault estimation based on the constrained zonotopic Kalman filter

Abstract

For solving the additive and multiplicative sensor faults in the constrained system with unknown but bounded noise, the constrained zonotopic Kalman filter-based additive sensor fault estimator and multiplicative sensor fault estimator are designed, respectively. In the fault estimation process, the states of the system are contained in the zonotopic sets estimated by the constrained zonotopic Kalman filter. The fault detection is carried out by judging whether the true value of the system's output is within the upper and lower bounds of its estimated zonotopic set. Once a fault is detected in the system, the corresponding sensor fault estimator can be used to estimate the additive or multiplicative sensor faults, and the corresponding zonotopic set and interval set can be obtained, respectively. Finally, comparative analyses of the proposed constrained zonotopic Kalman filter-based fault estimators and the zonotopic Kalman filter-based fault estimators in both numerical and case simulations prove the feasibility and effectiveness of the proposed algorithm and show the advantages of this algorithm in view of conservativeness.

Resilient observer design of sensor fault estimation for discrete‐time multi‐agent systems: A distributed approach

“…The fault estimation problem of descriptor switched systems was proposed in 29 . A novel sensor estimation approach was presented based on the constrained zonotopic Kalman filter in 30 . The fault estimation problem for linear discrete time‐variant systems with saturations was studied in 13 .…”

“…29 A novel sensor estimation approach was presented based on the constrained zonotopic Kalman filter in. 30 The H ∞ fault estimation problem for linear discrete time-variant systems with saturations was studied in. 13 An observer-based fault estimation was investigated based on T-S fuzzy models for a class of discrete-time nonlinear systems in.…”

Distributed cooperative fault detection and isolation for uncertain multi‐agent systems based on zonotope theory

“…In particular, system state interval estimation or FDI design by using zonotope theory has become one of the hottest research topics recently. 26,[35][36][37][38][39][40][41] For example, the state interval estimations of the load's orientation and position are given via zonotopes in Reference 36. Reference 37 propose a zonotope state interval estimation strategy for a descriptor linear parameter-varying system with uncertainties and measurement noises.…”

“…Zonotope theory is widely used in solving various problems including system state interval estimation problem, FDI problem, and predictive control problem and so on. In particular, system state interval estimation or FDI design by using zonotope theory has become one of the hottest research topics recently 26,35‐41 . For example, the state interval estimations of the load's orientation and position are given via zonotopes in Reference 36.…”