Online Active Fault Detection for Over-Actuated Systems With Prescribed Control Performance

Abstract

In the field of fault detection, active fault detection for dynamic systems is an emerging research topic. By redesigning the control input, active fault detection can enhance fault detection performance. In this study, the online active fault detection problem is investigated for over-actuated systems, where the control input is designed by considering both the prescribed control performance and the fault detection performance. A two-stage input design architecture is constructed, where the first stage is a virtual controller design and the second stage is a control allocation design. In the first stage, the virtual control input is designed by utilizing a prescribed performance function to fulfill the control requirement. In the second stage, a differential evolution method is adopted to obtain an optimal control allocation algorithm for improving the fault detection performance. The designed control input can both improve fault detection performance and achieve the prescribed control performance. Two cases, including a numerical example and a manned submersible propulsion system, are studied to support theoretical results. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In this study, the aim is to design a control input for over-actuated systems to obtain better fault detection performance while achieving prescribed control performance. To achieve it, a two-stage control input design architecture is constructed, where the first stage is a virtual controller design and the second stage is a control allocation design. In the first stage, choose a proper prescribed performance function and a sliding mode function to accomplish the transient and steady behavioral bounds on the tracking errors. In the second stage, design a special observer to generate the system residual signal, which is used for indicating system faults. Based on the residual signal, construct an index for the control allocation algorithm. Differential evolution algorithm is applied to obtain the optimal control allocation algorithm by maximizing the index. Thus the control allocation algorithm which can improve fault detection performance is designed. In this way, the input can improve fault detection performance without affecting system behavior. The proposed technique of this study can be applied to dynamic systems with input redundancy.