Dynamics and control of quadcopter using linear model predictive control approach

This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to tr...

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Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2017-12, Vol.270 (1), p.12007
Main Authors: Islam, M, Okasha, M, Idres, M M
Format: Article
Language:English
Subjects:
Actuators
Constraint modelling
Dynamic models
Nonlinearity
Optimal control
Predictive control
Trajectory control
Uncertainty
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Summary:This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators' saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/270/1/012007