Explicit Nonlinear Model Predictive Control for a Saucer-Shaped Unmanned Aerial Vehicle

Zhang, Xing; Wu, Sentang; Wu, Xiaolong

doi:10.1155/2013/706453

Cited by 3 publications

(2 citation statements)

References 20 publications

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“…The saucer-shaped UAV studied in this work is an improved version of the previous aerodynamic model mentioned in Ref. [31], as shown in Figure 1. The UAV is composed of a saucer-shaped lifting-body fuselage, two split drag rudders (SDRs) mounted on the trailing edge of each small wing and four tailerons (inboard and outboard).…”

Section: Model Description Of the Saucer-shaped Uavmentioning

confidence: 99%

Disturbance and Uncertainty Suppression Control for a Saucer-Shaped Unmanned Aerial Vehicle Based on Extended State Observer

et al. 2020

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For saucer-shaped unmanned aerial vehicles with blended wing bodies (BWBs), un-modelled coupling effect uncertainty and external disturbance missing the matching conditions have always been the concerns. To solve this flight control problem, this research has proposed a composite backstepping controller incorporated with a finite-time convergent differentiator and a nonlinear extended state observer (ESO). More specifically, the differentiator is employed to obtain the derivatives of the virtual control laws in finite-time and therefore eliminate the inherent “explosion of term” problem in backstepping. By the effective real-time estimation of ESO without the peaking value problem, the total effect of internal uncertainties and external disturbances is compensated in the control law design, which can dispense with parameter identification and model approximation. Furthermore, based on Lyapunov theory, it is proved rigorously that all the signals of the resulting closed-loop systems are bounded. In the final part of this paper, simulation results are presented to validate the effectiveness of the proposed control scheme.

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Section: Model Description Of the Saucer-shaped Uavmentioning

confidence: 99%

Disturbance and Uncertainty Suppression Control for a Saucer-Shaped Unmanned Aerial Vehicle Based on Extended State Observer

et al. 2020

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“…ENMPC law of the quadrotor ENMPC theory ENMPC was proposed by Wen-Hua Chen (Chen et al, 2003), which will be able to provide satisfactory tracking trajectories (Liu et al, 2011a, b) and have been further studied by many researchers (Liu et al, 2011a(Liu et al, , b, 2012Xing et al, 2013). The simplified nonlinear model can be described by the following equation:…”

Section: Nonlinear Quadrotor Modelmentioning

confidence: 99%

A Quantum-behaved Pigeon-Inspired Optimization approach to Explicit Nonlinear Model Predictive Controller for quadrotor

Xian

Chen

2018

IJICC

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Purpose The purpose of this paper is to simplify the Explicit Nonlinear Model Predictive Controller (ENMPC) by linearizing the trajectory with Quantum-behaved Pigeon-Inspired Optimization (QPIO). Design/methodology/approach The paper deduces the nonlinear model of the quadrotor and uses the ENMPC to track the trajectory. Since the ENMPC has high demand for the state equation, the trajectory needed to be differentiated many times. When the trajectory is complicate or discontinuous, QPIO is proposed to linearize the trajectory. Then the linearized trajectory will be used in the ENMPC. Findings Applying the QPIO algorithm allows the unequal distance sample points to be acquired to linearize the trajectory. Comparing with the equidistant linear interpolation, the linear interpolation error will be smaller. Practical implications Small-sized quadrotors were adopted in this research to simplify the model. The model is supposed to be accurate and differentiable to meet the requirements of ENMPC. Originality/value Traditionally, the quadrotor model was usually linearized in the research. In this paper, the quadrotor model was kept nonlinear and the trajectory will be linearized instead. Unequal distance sample points were utilized to linearize the trajectory. In this way, the authors can get a smaller interpolation error. This method can also be applied to discrete systems to construct the interpolation for trajectory tracking.

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A stochastic robustness controller for a saucer-shaped UAV based on quantum evolutionary algorithm

Zhang

et al. 2014

Proceedings of the 33rd Chinese Control Conference

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Explicit Nonlinear Model Predictive Control for a Saucer-Shaped Unmanned Aerial Vehicle

Cited by 3 publications

References 20 publications

Disturbance and Uncertainty Suppression Control for a Saucer-Shaped Unmanned Aerial Vehicle Based on Extended State Observer

Disturbance and Uncertainty Suppression Control for a Saucer-Shaped Unmanned Aerial Vehicle Based on Extended State Observer

A Quantum-behaved Pigeon-Inspired Optimization approach to Explicit Nonlinear Model Predictive Controller for quadrotor

A stochastic robustness controller for a saucer-shaped UAV based on quantum evolutionary algorithm

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