IEEE Sensors Journal · 2023 · 16 citations · 28 references
EngineeringMarine EngineeringSystems EngineeringFault ToleranceFault-tolerant SystemsShip ControlAutopilot SystemsFault DetectionFault-tolerant ControlMarine Automation SystemsState EstimationActive Fault-tolerant ControlFault Detection In Control SystemsFault Diagnosis In Steering SystemsFault EstimationFault-tolerant DesignFault-tolerant State EstimationState Estimation Under FaultsSteering System Fault Diagnosis
This article investigates the problem of fault estimation and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${H}_{\infty }$ </tex-math></inline-formula> fuzzy active fault-tolerant control design for ship steering autopilot (SSA) system with simultaneous partial states that are not easily measured, actuator (steering machine), and sensor (compass) faults. First, the Takagi–Sugeno (T–S) fuzzy model is employed to describe the nonlinear dynamics of SSA system, and the feasibility of the designed model is analyzed with the collected navigation data. Then, an auxiliary <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${H}_{\infty }$ </tex-math></inline-formula> fuzzy observer (AHFO) is introduced for asymptotic estimation of unknown states and faults. Using the observation information provided by the AHFO, an AHFO-based active fault-tolerant controller (AHFO-based AFTC) is designed for stabilizing the SSA system with steering and compass faults to achieve satisfactory control requirements, including stability and tracking performance. Finally, an example of ship course fault-tolerant control is conducted to verify the effectiveness of this method.
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