Abstract

This research is to develop set-point weighting-based dynamic integral sliding mode control with nonlinear full-order state observers to deal with nonlinear and underactuated coupled systems, and unforeseen circumstances of quadcopter UAVs systems. A comparative assessment through numerical simulations of sliding mode-based nonlinear observer approaches and Kalman filter is presented. These include quasi method, interval type-2 fuzzy logic system, super-twisting algorithm, higher order sliding mode observer, and extended Kalman filter. Chattering, noise rejection, estimation error and time required to track true states are evaluated to demonstrate the performance of each observer. In addition, to assess the proposed controller performance, maximum overshoot, rise time, chattering, and steady-state error are evaluated in relation to the use of each observer.

Highlights

  • Various controllers have been developed for performance enhancement of quadcopter unmanned aerial vehicles (UAVs)

  • Set-point weighting-based dynamic integral sliding mode control for quadcopter UAVs phenomenon following the use of SMC is still an issue to be resolved

  • high order sliding mode control (HOSMC) can reduce oscillation phenomenon in SMC adequately, but this method still cannot address the problem in n-th derivative states

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Summary

Introduction

Various controllers have been developed for performance enhancement of quadcopter UAVs. Some methods have been proposed to eliminate this phenomenon These include quasi sliding mode control (QuasiSMC) (Shtessel et al, 2010); interval type-2 fuzzy sliding mode control (IT2FSMC) (Firdaus and Tokhi, 2016); high order sliding mode control (HOSMC) (Ghabi, 2018); super-twisting algorithm of sliding mode control (STASMC) (Ibarra and Castillo, 2017); and dynamic sliding mode control (DSMC) (Liu and Wang, 2011). These methods can eliminate the problem of chattering, they have their associated shortcomings.

Quadcopter system model
Quadcopter control and observer design
Set-point weighting-based dynamic integral sliding mode control
Integral sliding surface design
Set-point weighting
Basic observer design
Sliding mode observer
Chattering avoidance: elimination and attenuation
Chattering elimination: quasi-sliding mode observer
Chattering elimination: sliding mode-based interval type-2 fuzzy observer
Chattering attenuation: super-twisting algorithm of sliding mode observer
Chattering attenuation: higher order sliding mode observer
Numerical simulation results
Without noise and no parameters mismatch
Observer methods
With noise and with parameters mismatch
Summary
Findings
Conclusion

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