Fault-tolerant control through a synthesis of model-predictive control and nonlinear inversion

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Abstract

By itself reconfigurable and fault-tolerant control is a challenging task. In general fault-tolerant control requires mechanisms to detect and identify a failure, furthermore, it must be flexible as to accommodate such a failure. In the more specific case of fault-tolerant flight control, several specific challenges exist according to [1]: flight control is a multi-variable control problem with strong cross-couplings, especially appearing after an asymmetric failure occurs; flight control is a nonlinear problem which means that trim values change with operating conditions, requiring continuous use of nonlinear or adaptive algorithms; an aircraft may become highly unstable after occurrence of a failure, leaving little time for reconfiguration; In order to tackle these challenges, we will introduce a control method that is globally valid, easily reconfigurable and above all, constrained. The solution that is presented here is a synthesis between model-predictive control (MPC) and a nonlinear dynamic inversion method (NDI). Section 11.2 provides the motivation for this setup, and furthermore, the section provides a clear introduction as to how both methods interact. Section 11.2.2 and 11.2.3 provide a discussion of the theory of MPC and dynamic inversion, whereas Section 11.2.4 on control allocation, and the mapping of constraints, provides the theory that is required to make the proposed combination of MPC and dynamic inversion interact correctly. Subsequently Section 11.3 introduces the relevant equations of motion of the benchmark aircraft and applies NDI theory to these. The chapter continues with the introduction of simulation results in Section 11.4 and wraps up with a discussion and conclusions in Section 11.5. © 2010 Springer-Verlag Berlin Heidelberg.

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Joosten, D. A., Van Den Boom, T. J. J., & Verhaegen, M. (2010). Fault-tolerant control through a synthesis of model-predictive control and nonlinear inversion. Lecture Notes in Control and Information Sciences, 399, 319–336. https://doi.org/10.1007/978-3-642-11690-2_11

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