Multiple Control Surface Failure Detection Via On-Line Filter Tuning Method

Abstract Elevator failure may have fatal consequences for fighter aircraft that are unstable due to their high manoeuvrability requirements. Many studies have been conducted in the literature using active and passive fault-tolerant control structures. However, these studies mostly include sophisticated controllers with high computational load that cannot work in real systems. Considering the multi-functionality and broad operational prospects of fighter aircraft, computational load is very important in terms of applicability. In this study, an integrated fault-tolerant control strategy with low computational load is proposed without sacrificing the ability to cope with failures. This control strategy switches between predetermined controllers in the case of failure. One of these controllers is designed to operate in a non-failure condition. This controller is a basic controller that requires very little computational effort. The other controller operates when an asymmetric elevator failure occurs. This controller is a robust fault-tolerant controller that can fly the aircraft safely in case of elevator failure. The switching is decided by a failure detection system. The proposed integrated fault-tolerant control system is verified by non-linear F-16 flight simulations. These simulations show that the proposed method can cope with failures but requires less computational load because it uses a conventional controller in the case of no failure.

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Design of Robust Approach for Failure Detection in Dynamic Control Systems

Recent Algorithms and Applications in Swarm Intelligence Research ◽

10.4018/978-1-4666-2479-5.ch013 ◽

2013 ◽

pp. 237-259

Author(s):

Gomaa Zaki El-Far

Keyword(s):

Nuclear Power ◽

Dynamic Control ◽

Control Process ◽

Failure Detection ◽

Global Optimum ◽

Sampling Time ◽

Nuclear Power Reactor ◽

Control Actions ◽

On Line ◽

Simulation Results

This paper presents a robust instrument fault detection (IFD) scheme based on modified immune mechanism based evolutionary algorithm (MIMEA) that determines on line the optimal control actions, detects faults quickly in the control process, and reconfigures the controller structure. To ensure the capability of the proposed MIMEA, repeating cycles of crossover, mutation, and clonally selection are included through the sampling time. This increases the ability of the proposed algorithm to reach the global optimum performance and optimize the controller parameters through a few generations. A fault diagnosis logic system is created based on the proposed algorithm, nonlinear decision functions, and its derivatives with respect to time. Threshold limits are implied to improve the system dynamics and sensitivity of the IFD scheme to the faults. The proposed algorithm is able to reconfigure the control law safely in all the situations. The presented false alarm rates are also clearly indicated. To illustrate the performance of the proposed MIMEA, it is applied successfully to tune and optimize the controller parameters of the nonlinear nuclear power reactor such that a robust behavior is obtained. Simulation results show the effectiveness of the proposed IFD scheme based MIMEA in detecting and isolating the dynamic system faults.

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