/MPC-quadcopter

Model Predictive Control for an autonomous quadcopter (UAV)

Primary LanguageMATLAB

MPC Quadcopter

Model Predictive Control for an autonomous quadcopter (UAV)

  • System modelling
    • State-Space model
    • Linearization
  • Controller design
    • PID SISO control approach
    • MPC MIMO control approach
    • Observers: Kalman filter
  • Simulation
    • PID simulation
    • MPC simulation (linear model)
    • Real-Time simulation (non-linear model)

(Under construction)

Model predictive control (MPC)

Quadcopter simulation

Algorithm

  • Initialization of the variables

  • Get the augmented incremental model and the parameters of the control trajectories vector (DeltaU) based on the state-space system, the control horizon (Nc) and prediction horizon (Np)

    • Augmented incremental model

    • Incremental control trajectory vector (DeltaU) obtained from the cost function minimization

  • Calculate the constant part of DeltaU

  • Control loop

    • Read input signal

    • Calculate the variable part of DeltaU

    • Add both parts and apply the receding horizon control extracting first element

    • Get the control signal

    • Get the incremental system state

Figures from [1]

MPC with output constraints

  • In the initialization variables:

    • Create M matrix

  • In the control loop:

    • Calculate the gamma matrix with the constraints of the output
    • Recalculate DeltaU from optimization with restrictions

    Constraint output / u / delta u:

Figures from [1]

References

[1] Sistemas de control en tiempo real para aplicaciones industriales: Teoría, problemas y prácticas - Ramón Guzmán 2020

[2] Dynamic Modeling and Control of a Quadrotor Using Linear and Nonlinear Approaches - H. M. Nabil ElKholy - 2014

[3] Decentralized Navigation of Multiple Quad-rotors using Model Predictive Control - I. Khan - 2017