| Summary: | The main objective of this paper is to develop an actuator and sensor fault estimation framework taking into account various uncertainty sources. In particular, these are divided into three groups: sensor measurement noise, process-external exogenous disturbances, as well as unknown fault dynamics. Unlike the approaches presented in the literature, here they are not processed in the same way but treated separately in a suitably tailored fashion. Finally, the approach resolves to minimizing their effect on the fault estimation error in either the <inline-formula> <math display="inline"> <semantics> <msub> <mi mathvariant="script">H</mi> <mn>2</mn> </msub> </semantics> </math> </inline-formula> or <inline-formula> <math display="inline"> <semantics> <msub> <mi mathvariant="script">H</mi> <mo>∞</mo> </msub> </semantics> </math> </inline-formula> sense. As a result, a mixed performance−based actuator fault estimation framework is obtained, along with its convergence conditions. The final part of the paper presents performance analysis results obtained for a DC servo-motor. Subsequently, another three-tank-system-based example is presented. In both cases, the proposed approach is compared with an alternative one, which clearly exhibits its superiority.
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