Nonlinear Integral Sliding Mode

  • Mirza Tariq HamayunEmail author
  • Christopher Edwards
  • Halim Alwi
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 61)


Many of the existing FTC schemes in the literature are based on linear plant representations and are therefore only valid in the vicinity of the designed trim point . Therefore, one of the main challenges for practical implementation, especially for aircraft, is to ensure good performance for a wide range of operating conditions . Some of the linear based designs can be extended to handle variations in operating conditions, but direct nonlinear methods such as nonlinear dynamic inversion  (NDI) and backstepping provide equally viable alternatives—with many benefits compared to the extended linear cases. One obvious benefit is the direct exploitation of the well-known aircraft equations of motion , which provides good and consistent performance throughout the flight envelope. This chapter presents a nonlinear fault tolerant scheme for longitudinal control of an aircraft system, comprising an integral sliding mode control allocation scheme and a backstepping structure. In fault-free conditions, the closed-loop system is governed by the backstepping controller and the integral sliding mode control allocation scheme only influences the performance if faults/failures occur in the primary control surfaces . In this situation the allocation scheme redistributes the control signals to the secondary control surfaces and the scheme is able to tolerate total failures in the primary actuator . A backstepping scheme taken from the existing literature is designed for flight path angle tracking (based on the nonlinear equations of motion ) and this is used as the underlying baseline controller . The efficacy of the scheme is demonstrated using the RECOVER benchmark model .


Control Surface Flight Path Angle Flight Envelope Horizontal Stabiliser Float Failure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Mirza Tariq Hamayun
    • 1
    Email author
  • Christopher Edwards
    • 2
  • Halim Alwi
    • 2
  1. 1.Department of Electrical EngineeringCOMSATS Institute of Information TechnologyLahorePakistan
  2. 2.College of Engineering Mathematics and Physical SciencesUniversity of ExeterExeterUK

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