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...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
Institute of Physics Publishing
2017
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/62289/ http://irep.iium.edu.my/62289/ http://irep.iium.edu.my/62289/ http://irep.iium.edu.my/62289/1/Islam_2017_IOP_Conf._Ser.%253A_Mater._Sci._Eng._270_012007.pdf http://irep.iium.edu.my/62289/7/62289%20Dynamics%20and%20control%20of%20quadcopter%20using%20linear%20model%20SCOPUS.pdf |
| 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. |
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