Publication
MPC fault-tolerant flight control case study: Flight 1862
Abstract
We demonstrate that the fatal crash of El Al Flight 1862 might have been avoided by using MPC-based fault-tolerant control. Simulation on a detailed nonlinear model shows that it is possible to reconfigure the controller so that the aircraft is flown successfully down to ground level, without entering the condition in which it was lost. We use a reference-model based approach, in which an MPC controller attempts to restore the original functionality of the pilot’s controls. For the purposes of simulation, we emulate the pilot by another MPC controller, running at a lower sampling rate. We assume in this paper that an FDI function delivers information about actuator damage, and about changes to aerodynamic coefficients in the failed condition.
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Related concepts (12)
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Model predictive control (MPC) is an advanced method of process control that is used to control a process while satisfying a set of constraints. It has been in use in the process industries in chemical plants and oil refineries since the 1980s. In recent years it has also been used in power system balancing models and in power electronics. Model predictive controllers rely on dynamic models of the process, most often linear empirical models obtained by system identification.
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Control theory is a field of control engineering and applied mathematics that deals with the control of dynamical systems in engineered processes and machines. The objective is to develop a model or algorithm governing the application of system inputs to drive the system to a desired state, while minimizing any delay, overshoot, or steady-state error and ensuring a level of control stability; often with the aim to achieve a degree of optimality. To do this, a controller with the requisite corrective behavior is required.
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